{
  "version": 1,
  "updated": "2026-08-18",
  "tiers": [
    {
      "id": "nano",
      "label": "Nano",
      "blurb": "Single consumer GPU / laptop",
      "models": [
        {
          "id": "qwen3.5-9b",
          "name": "Qwen3.5-9B",
          "role": null,
          "description": "Dense 9B with vision encoder, hybrid Gated DeltaNet/attention, 262K context",
          "params": "9B dense, hybrid Gated DeltaNet/attention",
          "active_params_b": null,
          "context_tokens": 262144,
          "license": "Apache-2.0",
          "multimodal": true,
          "notes": [
            "Listed as \"qwen3.6-9b\" in some sources — no 3.6 9B exists; the 9B dense is Qwen3.5",
            "Thinks by default — serve with --reasoning-parser qwen3",
            "Needs bleeding-edge runtimes (vLLM nightly)",
            "Text-only serving: --language-model-only frees vision memory",
            "GGUF needs mmproj-*.gguf for vision",
            "No official FP8 or NVFP4 — RedHatAI (FP8) and community (NVFP4) only"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "Qwen/Qwen3.5-9B",
              "official": true,
              "size_gb": 19.3,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "RedHatAI/Qwen3.5-9B-FP8-dynamic",
              "official": false,
              "source": "RedHatAI",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "kaitchup/Qwen3.5-9B-autoround-NVFP4",
              "official": false,
              "source": "kaitchup",
              "size_gb": null,
              "caveat": "community quant"
            },
            {
              "format": "q4",
              "repo": "unsloth/Qwen3.5-9B-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "Dense · hybrid Gated DeltaNet + attention",
          "total_params_b": 9.0,
          "intelligence_index": 21.8,
          "agentic_index": 7.0
        },
        {
          "id": "gemma-4-e2b",
          "name": "Gemma 4 E2B",
          "role": null,
          "description": "2.3B effective multimodal (text+image+audio in) with 128K context",
          "params": "5.1B total w/ Per-Layer Embeddings (2.3B effective)",
          "active_params_b": null,
          "context_tokens": 131072,
          "license": "Apache-2.0",
          "multimodal": true,
          "notes": [
            "NVFP4 needs vLLM ≥ 0.25 + flashinfer — let vLLM auto-select the kernel (not Marlin)",
            "Google also ships official QAT 4-bit GGUFs (google/gemma-4-E2B-it-qat-q4_0-gguf) as a creator-official alternative",
            "No official FP8 — community FP8-dynamic only; official 4-bit path is Google's own QAT GGUFs"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "google/gemma-4-E2B-it",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "leon-se/gemma-4-E2B-it-FP8-Dynamic",
              "official": false,
              "source": "leon-se",
              "size_gb": null,
              "caveat": "community quant"
            },
            {
              "format": "nvfp4",
              "repo": "unsloth/gemma-4-E2B-it-NVFP4",
              "official": false,
              "source": "unsloth",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/gemma-4-E2B-it-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "google/gemma-4-E2B-it-qat-q4_0-gguf",
              "official": true,
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "Dense · Per-Layer Embeddings",
          "total_params_b": 5.1,
          "intelligence_index": 9.5,
          "agentic_index": null
        },
        {
          "id": "lfm2.5-2.6b",
          "name": "LFM2.5-2.6B",
          "role": "fast",
          "description": "Liquid's 2.6B hybrid built for on-device agents — 128K context, tool use, and RAG",
          "params": "2.69B dense, LFM2 hybrid conv/attention",
          "architecture": "Dense · LFM2 hybrid (short conv + GQA)",
          "total_params_b": 2.69,
          "active_params_b": null,
          "context_tokens": 131072,
          "license": "LFM Open License v1.0",
          "multimodal": false,
          "notes": [
            "Built for on-device agentic workloads — tool use, extraction, RAG; not a coding or knowledge model",
            "Pre-trained on ~34T tokens, mid-trained to a 128K window",
            "Ships official GGUF, MLX, and ONNX builds alongside the safetensors checkpoint",
            "No official FP8 or NVFP4 — it is small enough that BF16 fits almost anywhere"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "LiquidAI/LFM2.5-2.6B",
              "official": true,
              "size_gb": 5.4,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "LiquidAI/LFM2.5-2.6B-GGUF",
              "official": true,
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": 1.7,
              "caveat": null
            }
          ],
          "intelligence_index": null,
          "agentic_index": null
        }
      ]
    },
    {
      "id": "mini",
      "label": "Mini",
      "blurb": "Single 24–48 GB GPU",
      "models": [
        {
          "id": "gemma-4-26b-a4b",
          "name": "Gemma 4 26B A4B",
          "role": "fast",
          "description": "Multimodal MoE with only 3.8B active params — 3–5× faster decode than dense picks",
          "params": "25.2B total MoE",
          "active_params_b": 3.8,
          "context_tokens": 262144,
          "license": "Gemma",
          "multimodal": true,
          "notes": [
            "MoE ≠ small download — all weights must still fit in memory",
            "Do NOT use vLLM --quantization fp8 on-the-fly with the BF16 repo (broken output — use the RedHatAI checkpoint)",
            "NVFP4 on non-Blackwell falls back to Marlin and is slower than FP8",
            "GGUF has a known ROCm infinite-loop bug; bartowski publishes alternative imatrix GGUFs"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "google/gemma-4-26B-A4B-it",
              "official": true,
              "size_gb": 52,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "RedHatAI/gemma-4-26B-A4B-it-FP8-Dynamic",
              "official": false,
              "source": "RedHatAI",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "nvidia/Gemma-4-26B-A4B-NVFP4",
              "official": false,
              "source": "nvidia",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/gemma-4-26B-A4B-it-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_M*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "MoE · multimodal",
          "total_params_b": 25.2,
          "intelligence_index": 26.1,
          "agentic_index": 11.0
        },
        {
          "id": "gemma-4-31b",
          "name": "Gemma 4 31B",
          "role": "smart",
          "description": "Dense 31B with 262K context — the higher-quality dense pick in this tier",
          "params": "31B dense",
          "active_params_b": null,
          "context_tokens": 262144,
          "license": "Gemma",
          "multimodal": false,
          "notes": [
            "FP8-block (W8A8, better accuracy) or FP8-dynamic, both need sm_89+",
            "NVFP4 is Blackwell-only",
            "Unsloth repo includes MTP draft GGUFs for speculative decoding"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "google/gemma-4-31B-it",
              "official": true,
              "size_gb": 62,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "RedHatAI/gemma-4-31B-it-FP8-block",
              "official": false,
              "source": "RedHatAI",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "nvidia/Gemma-4-31B-IT-NVFP4",
              "official": false,
              "source": "nvidia",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/gemma-4-31B-it-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "Dense",
          "total_params_b": 31.0,
          "intelligence_index": 29.7,
          "agentic_index": 14.4
        },
        {
          "id": "qwen3.6-35b-a3b",
          "name": "Qwen3.6-35B-A3B",
          "role": "fast",
          "description": "256-expert MoE with only 3B active params and MTP speculative decoding built in",
          "params": "35B MoE, 256 experts",
          "active_params_b": 3,
          "context_tokens": 262144,
          "license": "Apache-2.0",
          "multimodal": false,
          "notes": [
            "MTP built in (usable as speculative decoding)",
            "Needs vLLM ≥ 0.19 / SGLang ≥ 0.5.10",
            "GGUF arch qwen35moe — older llama.cpp won't load it",
            "Q4_K_M ≈ 20 GB"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "Qwen/Qwen3.6-35B-A3B",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "Qwen/Qwen3.6-35B-A3B-FP8",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "unsloth/Qwen3.6-35B-A3B-NVFP4",
              "official": false,
              "source": "unsloth",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/Qwen3.6-35B-A3B-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_M*.gguf"
              ],
              "size_gb": 20,
              "caveat": null
            }
          ],
          "architecture": "MoE · 256 experts + MTP",
          "total_params_b": 35.0,
          "intelligence_index": 32.1,
          "agentic_index": 21.6
        },
        {
          "id": "qwen3.8-27b",
          "name": "Qwen3.8-27B",
          "role": "smart",
          "description": "Dense 27B vision-language model with 262K context — the strongest model that still fits one 24 GB GPU at Q4",
          "params": "27.8B dense + vision encoder",
          "architecture": "Dense · Gated DeltaNet + Gated Attention, native VLM",
          "total_params_b": 27.8,
          "active_params_b": null,
          "context_tokens": 262144,
          "license": "Apache-2.0",
          "multimodal": true,
          "notes": [
            "Native vision-language: images and hour-scale video, not just text",
            "Thinking is on by default; disable per request and tune depth with reasoning_effort",
            "Text-only serving: --language-model-only frees the vision encoder's memory",
            "Q4_K_M ≈ 17 GB, so a 24 GB GPU is the realistic floor",
            "Official BF16 and FP8 from Qwen; NVFP4 and AWQ are community builds"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "Qwen/Qwen3.8-27B",
              "official": true,
              "size_gb": 55.6,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "Qwen/Qwen3.8-27B-FP8",
              "official": true,
              "size_gb": 30.9,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "unsloth/Qwen3.8-27B-NVFP4",
              "official": false,
              "source": "unsloth",
              "size_gb": 23.4,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/Qwen3.8-27B-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": 17.1,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "cyankiwi/Qwen3.8-27B-AWQ-INT4",
              "official": false,
              "source": "cyankiwi",
              "size_gb": 21.0,
              "caveat": "AWQ INT4 for vLLM, not GGUF"
            }
          ],
          "intelligence_index": 52.0,
          "agentic_index": 50.9
        }
      ]
    },
    {
      "id": "medium",
      "label": "Medium",
      "blurb": "Large unified memory / multi-GPU — 200B+ MoEs",
      "models": [
        {
          "id": "step-3.7-flash",
          "name": "Step 3.7 Flash",
          "role": null,
          "description": "198B MoE with 11B active — runs on a 128 GB Mac Studio or DGX Spark at Q4",
          "params": "198B MoE",
          "active_params_b": 11,
          "context_tokens": 262144,
          "license": "Apache-2.0",
          "multimodal": false,
          "notes": [
            "Even Q4 needs ≥120 GB unified memory (Mac Studio 128 GB, DGX Spark)",
            "llama.cpp requires StepFun's fork (branch step3.7)",
            "vLLM needs the dedicated vllm/vllm-openai:stepfun37 image + --trust-remote-code --disable-cascade-attn --reasoning-parser step3p5",
            "Rare: StepFun ships its own NVFP4"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "stepfun-ai/Step-3.7-Flash",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "stepfun-ai/Step-3.7-Flash-FP8",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "stepfun-ai/Step-3.7-Flash-NVFP4",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/Step-3.7-Flash-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_XL*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "stepfun-ai/Step-3.7-Flash-GGUF",
              "official": true,
              "allow_patterns": [
                "*Q4_K_S*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "MoE",
          "total_params_b": 198.0,
          "intelligence_index": 30.9,
          "agentic_index": 21.7
        },
        {
          "id": "deepseek-v4-flash-0731",
          "name": "DeepSeek V4 Flash 0731",
          "role": null,
          "description": "304B MoE with 1M context and a built-in speculative decoding module — the official release, superseding the preview",
          "params": "304B MoE, 256 routed experts (top-6)",
          "architecture": "MoE · 256 experts, top-6, + speculative decoder",
          "total_params_b": 304.0,
          "active_params_b": 13.0,
          "context_tokens": 1048576,
          "license": "MIT",
          "multimodal": false,
          "notes": [
            "Official 0731 release — supersedes the DeepSeek-V4-Flash preview",
            "Ships with a speculative decoding module attached (same structure as the DSpark build)",
            "No BF16 checkpoint exists — natively FP4-experts + FP8 mixed by design",
            "GGUF needs recent llama.cpp; Unsloth ships the corrected chat template",
            "GGUF UD-Q4_K_XL is 5 shards, ~155 GB total"
          ],
          "variants": [
            {
              "format": "fp8",
              "repo": "deepseek-ai/DeepSeek-V4-Flash-0731",
              "official": true,
              "size_gb": 166.9,
              "caveat": "native FP4-experts + FP8 mixed checkpoint"
            },
            {
              "format": "fp8",
              "repo": "AtlasCloud/DeepSeek-V4-Flash-0731-FP8-DSpark",
              "official": false,
              "source": "AtlasCloud",
              "size_gb": 307.4,
              "caveat": "full W8A8 repack"
            },
            {
              "format": "nvfp4",
              "repo": "MJPansa/DeepSeek-V4-Flash-0731-NVFP4",
              "official": false,
              "source": "MJPansa",
              "size_gb": 175.6,
              "caveat": "community quant"
            },
            {
              "format": "q4",
              "repo": "unsloth/DeepSeek-V4-Flash-0731-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_XL*.gguf"
              ],
              "size_gb": 155.1,
              "caveat": null
            }
          ],
          "intelligence_index": 51.8,
          "agentic_index": 48.4
        },
        {
          "id": "motif-3",
          "name": "Motif 3",
          "role": null,
          "description": "314B MoE with only 13.2B active — fine-grained 384-expert routing, 256K context, and a built-in MTP head",
          "params": "314B MoE, 384 routed experts (top-8) + 1 shared",
          "architecture": "MoE · GDLA attention, 384 experts top-8, MTP head",
          "total_params_b": 314.0,
          "active_params_b": 13.2,
          "context_tokens": 262144,
          "license": "MIT",
          "multimodal": false,
          "notes": [
            "Grouped Differential Latent Attention (GDLA) with a compressed KV representation",
            "MTP head enables self-speculative decoding out of the box",
            "53 layers (2 dense + 51 MoE), 220,160-token vocabulary, native 256K context",
            "BF16 ≈ 630 GB — the NVFP4 build from Motif is the practical multi-GPU path",
            "Custom arch (model_type Motif) needs --trust-remote-code and a recent runtime"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "Motif-Technologies/Motif-3",
              "official": true,
              "size_gb": 629.7,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "0ppxnhximxr/Motif-3-FP8",
              "official": false,
              "source": "0ppxnhximxr",
              "size_gb": 321.7,
              "caveat": "community quant"
            },
            {
              "format": "nvfp4",
              "repo": "Motif-Technologies/Motif-3-NVFP4",
              "official": true,
              "size_gb": 186.9,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "AesSedai/Motif-3-GGUF",
              "official": false,
              "source": "AesSedai",
              "allow_patterns": [
                "*Q4_K_M*.gguf"
              ],
              "size_gb": 197.0,
              "caveat": "5 shards"
            }
          ],
          "intelligence_index": 47.4,
          "agentic_index": 37.6
        }
      ]
    },
    {
      "id": "large",
      "label": "Large",
      "blurb": "Datacenter-class only",
      "models": [
        {
          "id": "minimax-m3",
          "name": "MiniMax M3",
          "role": null,
          "description": "~428B MoE with 23B active and 1M context — needs dedicated vLLM image",
          "params": "~428B MoE",
          "active_params_b": 23,
          "context_tokens": 1000000,
          "license": "MiniMax",
          "multimodal": false,
          "notes": [
            "Only official FP8 is MXFP8 microscaling (needs framework support)",
            "vLLM serving needs the vllm/vllm-openai:minimax-m3 image, --trust-remote-code, minimax_m3 parsers",
            "NVFP4 requires --block-size 128",
            "GGUF ships as 7 shards, ~240 GB total"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "MiniMaxAI/MiniMax-M3",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "MiniMaxAI/MiniMax-M3-MXFP8",
              "official": true,
              "size_gb": null,
              "caveat": "MXFP8 microscaling, not W8A8"
            },
            {
              "format": "nvfp4",
              "repo": "nvidia/MiniMax-M3-NVFP4",
              "official": false,
              "source": "nvidia",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/MiniMax-M3-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_M*.gguf"
              ],
              "size_gb": 240,
              "caveat": null
            }
          ],
          "architecture": "MoE",
          "total_params_b": 428.0,
          "intelligence_index": 45.4,
          "agentic_index": 36.1
        },
        {
          "id": "glm-5.2",
          "name": "GLM 5.2",
          "role": null,
          "description": "753B MoE with ~40B active and 1M context — NVIDIA evals show NVFP4 ≈ FP8 parity",
          "params": "753B MoE",
          "active_params_b": 40,
          "context_tokens": 1000000,
          "license": "MIT",
          "multimodal": false,
          "notes": [
            "BF16 ≈ 1.5 TB",
            "NVIDIA's evals show NVFP4 ≈ FP8 parity (GPQA 89.39 vs 89.52)",
            "NVFP4 needs vLLM ≥ 0.23 / --quantization modelopt_fp4, --trust-remote-code, transformers ≥ 5.3",
            "Base repo is the chat model (no -Instruct suffix)"
          ],
          "variants": [
            {
              "format": "bf16",
              "repo": "zai-org/GLM-5.2",
              "official": true,
              "size_gb": 1500,
              "caveat": null
            },
            {
              "format": "fp8",
              "repo": "zai-org/GLM-5.2-FP8",
              "official": true,
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "nvfp4",
              "repo": "nvidia/GLM-5.2-NVFP4",
              "official": false,
              "source": "nvidia",
              "size_gb": null,
              "caveat": null
            },
            {
              "format": "q4",
              "repo": "unsloth/GLM-5.2-GGUF",
              "official": false,
              "source": "unsloth",
              "allow_patterns": [
                "*UD-Q4_K_M*.gguf"
              ],
              "size_gb": null,
              "caveat": null
            }
          ],
          "architecture": "MoE",
          "total_params_b": 753.0,
          "intelligence_index": 52.6,
          "agentic_index": 45.7
        }
      ]
    }
  ],
  "intelligence_source": "Artificial Analysis Intelligence Index, retrieved 2026-08-18"
}