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 4090. 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
Granite 4.1 3B
Dense, small, enterprise-flavoured: tool calling and instruction following, no thinking mode.
 29 Apr 2026 3.4B Q4_K_M 1.9 GB 128K Apache 2.0 319 tok/s Check · Hardware
Ling 3.0 Tiny 7.9B-A1.3B New
An 8B MoE with 1.3B active and a latent KV cache on only 6 of 24 layers — reasoning and tool use sized for Apple Silicon and edge boxes.
 10 Aug 2026 7.9B MoE Q4_K_M 4.4 GB 128K MIT 321 tok/s Check · Hardware
Fara 7B
A web computer-use agent on a Qwen2.5-VL base — it clicks, fills forms and stops for permission. Not a chat model; size it like an 8B with vision.
 24 Nov 2025 8.29B Q4_K_M 4.7 GB 125K MIT 131 tok/s Check · Hardware
Granite 4.1 8B
Matches the old Granite 4.0 32B MoE at a quarter of the size. Fast, Apache 2.0, no reasoning traces.
 29 Apr 2026 8.79B Q4_K_M 4.9 GB 128K Apache 2.0 123 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 115 tok/s Check · Hardware
gpt-oss 20B
Ships natively in MXFP4, so the 4-bit weights are the reference weights, not a lossy copy. Fits 16 GB.
 Aug 2025 20.9B MoE MXFP4 10.8 GB 128K Apache 2.0 126 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 45 tok/s 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 39 tok/s 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 39 tok/s Check · Hardware
Granite 4.1 30B
The largest Granite. Dense 29B at Q4 is a comfortable 24 GB fit.
 29 Apr 2026 28.9B Q4_K_M 16.3 GB 128K Apache 2.0 38 tok/s 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 36 tok/s 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 2.0 126 tok/s 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 139 tok/s Check · Hardware
Nemotron 3.5 Lightning 30B-A3B New
Mamba-2 + MoE hybrid built for the execution layer of agents: only 6 attention blocks, so the KV cache is almost free. Weights, data and recipe all open.
 11 Aug 2026 31.6B MoE Q4_K_M 17.8 GB 256K OpenMDW-1.1 130 tok/s 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 2.0 126 tok/s 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 126 tok/s Check · Hardware
gpt-oss 120B
Designed to land on one 80 GB card. Only ~5B parameters are active per token.
 Aug 2025 117B MoE MXFP4 60.5 GB 128K Apache 2.0 won't fit Check · Hardware
Nemotron 3 Super 120B-A12B
The open-training-data 120B. Same hybrid layout as Lightning, so 128K context costs under a gigabyte.
 Mar 2026 124B MoE Q4_K_M 69.7 GB 256K NVIDIA Open Model 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
Qwen3.5 397B-A17B
Flagship-class at 17B active. A 256 GB Mac Studio or a multi-GPU box at Q4.
 16 Feb 2026 403B MoE Q4_K_M 226.6 GB 256K Apache 2.0 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
Qwen3.8 2.4T-A95B New
The first open Qwen-Max-class flagship. Listed as the honest ceiling: nothing short of a rack runs it.
 12 Aug 2026 2446B MoE Q4_K_M 1375.4 GB 256K Qwen3.8-Max License 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.