Mistral Small 4 119B (2603)
Mistral Small 4 119B (2603) by Mistral AI (119B parameters, MoE with 6.5B active per token). At Q4_K_M with an 8K context it needs about 71.2 GiB of memory. A 119B MoE with 6.5B active and a compressed (MLA) KV cache; at 4-bit it needs a 72 GB card or a 96 GB unified-memory machine. There is no Ollama tag for it yet.
Last updated: 2026-10-13
Model facts
Memory needed
Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.
| Quantization | 4K context | 8K context | 32K context |
|---|---|---|---|
| Q4_K_M | 71.1 GiB | 71.2 GiB | 71.8 GiB |
| Q5_K_M | 83.4 GiB | 83.4 GiB | 84.0 GiB |
| Q6_K | 96.4 GiB | 96.5 GiB | 97.1 GiB |
| Q8_0 | 124.2 GiB | 124.3 GiB | 124.8 GiB |
| FP16 | 233.3 GiB | 233.4 GiB | 233.9 GiB |
Which hardware runs it
Best quantization that fits each device with a 8K context. Estimates, not benchmarks. See the methodology.
Frequently asked questions
How much VRAM does Mistral Small 4 119B (2603) need?
With an 8K context, about 71.2 GiB at Q4_K_M and 124.3 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.
Can Mistral Small 4 119B (2603) run on an GeForce RTX 4090?
Mistral Small 4 119B (2603) does not fit on the GeForce RTX 4090 (24 GB), even at Q4_K_M with an 8K context.
Can I run Mistral Small 4 119B (2603) on a Mac?
Yes. Mistral Small 4 119B (2603) fits on the M3 Ultra (96 GB) at Q4_K_M with an 8K context, using about 71.2 GiB, at an estimated 135 tokens/s.
Can Mistral Small 4 119B (2603) be used commercially?
Mistral Small 4 119B (2603) is released under Apache-2.0. The licence allows commercial use (read its conditions).