Mistral · Open weights
Mistral Small 4 119B
Mistral Small 4 is a hybrid MoE model that unifies instruct, reasoning, and coding behavior in a single multimodal model. It supports text and image input, native function calling, JSON output, and per-request reasoning effort controls.
- Reasoning
- Tools
- Vision
- Structured output
- Input
- Text, Images
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.40
- Output
- $1.40
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 16.4K
- Average output (7 days)
- 92 tokens
- Longer than 9% of 468 models
Side by side
Mistral Small 4 119B compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Mistral Small 4 119BMistralThis model | Sarvam 105BsarvamRemove | |
|---|---|---|
| Provider | Mistral | sarvam |
| Discovery tier | Open weights | Efficient |
| Added | Mar 16, 2026 | May 12, 2026 |
| Limits | ||
| Context window | 262.14KBest | 131.07K |
| Max output | 16.38KBest | 4.1K |
| Average output | 92 tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.40 | $0.054Best |
| Output | $1.40 | $0.21Best |
| Cache read | — | $0.0336 |
| Performance | ||
| Throughput | 128.8 tok/s | — |
| Time to first token | 0.7 s | — |
| Request success (24h) | 99.6% | — |
| Benchmark indexes | ||
| Intelligence Index | 9.0Best | 8.8 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | No |
| Reasoning effort | — | low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Mistral Small 4 119B
- Sarvam 105B
Intelligence Index
- Mistral Small 4 119B9.0
- Sarvam 105B8.8
Mistral Small 4 119B: Better than 16% of 326 scored models
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Mistral Small 4 119B: 28.3%Top
- Sarvam 105B: 0.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Mistral Small 4 119B: 3.8%
- Sarvam 105B: 11.0%Top
GPQA Diamond
Graduate-level science questions
- Mistral Small 4 119B: 57.1%
- Sarvam 105B: 73.8%Top
IFBench
Following precise output instructions
- Mistral Small 4 119B: 32.8%
- Sarvam 105B: 34.4%Top
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Mistral Small 4 119B: 10.6%Top
- Sarvam 105B: 1.5%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Mistral Small 4 119B: 18.4%
- Sarvam 105B: 46.8%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Mistral Small 4 119B: 28.3%Top
- Sarvam 105B: 0.0%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 128.8 tok/s
- Faster than 70% of 254 models
- Time to first token
- 0.7 s
- Quicker than 99% of 254 models
- Prompt cache hits
- 16.9%
- Request success (24h)
- 99.6%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mistralai/mistral-small-4-119b-2603",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="mistralai/mistral-small-4-119b-2603",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Mistral
Related models
Other Mistral models, starting with the same family.