Models

76 open-weight models, sized

Updated 21 Aug 2026 5 new this week, 14 this month

Parameter counts, layer counts and attention shapes are read from each model's own config, because the KV-cache arithmetic depends on them exactly. Sizes below are at Q4_K_M and 8K context against a GeForce RTX 3060 12 GB. Missing a model that shipped this week? Open an issue — the table is hand-maintained.

AllGeneral assistantCodingReasoning & mathsWritingVisionAgents & tool useTranslationLow latencyLong context
By sizeNewest first
RTX 4090RTX 3060 12 GBRX 7900 XTXM3 Max · 64 GB
ModelReleasedParamsQuantWeightsMax contextLicenceOn this rig
Qwen3.5 4B
The 8 GB coding agent. Q4 lands near 3.4 GB, leaving room for a real context window.
 28 Feb 2026 4.66B Q4_K_M 2.6 GB 256K Apache 2.0 83 tok/s Check · Hardware
Qwen2.5-Coder 7B
The standard local autocomplete model — small enough to keep resident all day, and still the best FIM model under 8B.
 Nov 2024 7.62B Q4_K_M 4.3 GB 128K Apache 2.0 51 tok/s Check · Hardware
Ornith 1.5 9B New this week
The small Ornith: a coding-agent reasoning build on the Qwen3.5 9B architecture. Same VRAM as its base, thinks before every answer.
 19 Aug 2026 9.41B Q4_K_M 5.3 GB 256K MIT 41 tok/s Check · Hardware
Qwen3.5 9B
The default for 8–12 GB cards in 2026: beats every older 8B on every published benchmark, with vision.
 28 Feb 2026 9.65B Q4_K_M 5.4 GB 256K Apache 2.0 40 tok/s Check · Hardware
Qwen2.5-Coder 14B
Noticeably better at whole-file edits than the 7B, still comfortable on 12 GB.
 Nov 2024 14.8B Q4_K_M 8.3 GB 128K Apache 2.0 26 tok/s Check · Hardware
Devstral Small 2 24B
Built for software-engineering agents (OpenHands, Cline). Dense 24B, 384K window. Not in the Ollama library.
 Dec 2025 24B Q4_K_M 13.5 GB 384K Apache 2.0 offload Check · Hardware
Qwen3.8 27B New this week
The current default local Qwen: dense 27B, text + image + video, 262K context. Only 16 of its 64 blocks keep a KV cache, so long context is cheap.
 14 Aug 2026 27.8B Q4_K_M 15.6 GB 256K Apache 2.0 offload Check · Hardware
Qwen3.6 27B
The 24 GB coding pick of spring 2026 (77.2 SWE-bench Verified). Same shape as 3.8, one generation behind.
 22 Apr 2026 27.8B Q4_K_M 15.6 GB 256K Apache 2.0 offload Check · Hardware
Muse Glimmer 30B New
Meta's first open weights since Llama 4: a dense 30B distilled from Muse Spark for always-on local agents. Two KV heads keep the cache small.
 10 Aug 2026 29.8B Q4_K_M 16.8 GB 128K Apache 2.0 offload Check · Hardware
Qwen3 Coder 30B-A3B
Agentic coding MoE with a 256K native window. Still the most-downloaded local code model.
 Jul 2025 30.5B MoE Q4_K_M 17.1 GB 256K Apache 2.0 offload Check · Hardware
GLM-4.7-Flash 30B-A3B
MIT-licensed 30B-A3B tuned for agentic coding, with a DeepSeek-style latent KV cache. 60–80 tok/s reported on a 4090.
 20 Jan 2026 31.2B MoE Q4_K_M 17.5 GB 198K MIT offload Check · Hardware
Qwen2.5-Coder 32B
The first local code model that felt competitive with hosted assistants. Qwen3.8 27B is smaller and far ahead on agentic work.
 Nov 2024 32.8B Q4_K_M 18.4 GB 128K Apache 2.0 offload Check · Hardware
Qwen3.6 35B-A3B
Mixture of experts with ~3B active: the fastest serious model a 24 GB card runs, and the best MoE under 40B on agentic coding.
 16 Apr 2026 35.9B MoE Q4_K_M 20.2 GB 256K Apache 2.0 offload Check · Hardware
Ornith 1.5 35B-A3B New this week
A reasoning-first MIT build on the Qwen3.6 35B-A3B architecture (thinks before every answer). Same VRAM as its base.
 19 Aug 2026 35.9B MoE Q4_K_M 20.2 GB 256K MIT offload Check · Hardware
Mistral Small 4 119B-A6B
Instruct, reasoning, vision and code in one 119B MoE. A latent KV cache (320 wide) keeps context cheap; the weights still want 64 GB+.
 17 Mar 2026 119B MoE Q4_K_M 66.9 GB 256K Apache 2.0 won't fit Check · Hardware
Ling 3.0 Flash 124B-A5B New
A 124B hybrid (5 linear-attention layers per MLA layer) with 5.1B active: SWE-bench Pro 56.6 and AIME 93 claimed. Built for 96–128 GB machines.
 2 Aug 2026 124B MoE Q4_K_M 69.7 GB 256K MIT won't fit Check · Hardware
Qwen3.5 122B-A10B
The 96–128 GB unified-memory model: 122B of knowledge at 10B-active speed.
 24 Feb 2026 125B MoE Q4_K_M 70.3 GB 256K Apache 2.0 won't fit Check · Hardware
DeepSeek V4 Flash 284B-A13B New
The V4 that 128 GB machines can actually run at Q3. Cache is modelled as a 576-wide latent; V4 compresses it further at long context, so this is conservative.
 31 Jul 2026 284B MoE Q4_K_M 159.7 GB 1024K MIT won't fit Check · Hardware
Ornith 1.5 397B-A17B New this week
The flagship Ornith on the Qwen3.5 397B-A17B architecture, MIT-licensed. A 256 GB Mac Studio at Q4, and it is in the Ollama library.
 19 Aug 2026 397B MoE Q4_K_M 223.2 GB 256K MIT won't fit Check · Hardware
GLM-5.2 744B-A40B
The strongest all-round open-weight model of mid-2026 on most public boards. Listed as a ceiling: 512 GB of unified memory at Q4.
 13 Jun 2026 753B MoE Q4_K_M 423.4 GB 1024K MIT won't fit Check · Hardware
Kimi K2.6 1T-A32B
The open coding-agent benchmark leader of spring 2026 (80.2 SWE-bench). A 512 GB Mac Studio pair, or a ceiling.
 20 Apr 2026 1027B MoE Q4_K_M 577.5 GB 256K Modified MIT won't fit Check · Hardware
DeepSeek V4 Pro 1.6T-A49B New
The 0813 refresh of the V4 flagship. Included as the honest ceiling; a terabyte of weights at Q4.
 13 Aug 2026 1650B MoE Q4_K_M 927.8 GB 1024K MIT won't fit Check · Hardware
Kimi K3 2.8T-A104B New
The largest open-weight model ever published. 69 of 93 blocks are linear attention, so its cache is tiny; its 2.8T weights are the problem.
 27 Jul 2026 2780B MoE Q4_K_M 1563.2 GB 1024K Modified MIT won't fit Check · Hardware

Weight sizes are computed from the parameter count and the quantisation's effective bits per weight, not read off a file listing — expect them to land within a few percent of the GGUF you actually download. The method, in full.