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  1. Models
  2. Text
  3. Mistral

Mistral Small 4 119B Thinking

Mistral Small 4 with reasoning enabled (reasoning_effort=high). A hybrid MoE model with deep step-by-step reasoning for complex prompts, coding, and multi-step problem solving.

  • Reasoning
  • Vision
  • Tool Calling
  • Structured Output

Added Mar 17, 2026

Model weights

Pricing

Auto routing · per 1M tokens
Input
$0.40
Output
$1.40
Cache read
$0.20
Compare provider prices

Specifications

Context window
262.1K
Max output
16.4K
Parameters
119B / 6B
Total / active

Benchmarks

Leaderboard results

These leaderboards tested Mistral Small 4 119B, another version of this model.

BenchmarkScoreRank on NanoGPT
EQ-Bench

EQ-Bench data, MIT · Updated Nov 14, 2026

Longform Writing

43.2

#77 of 97

UGI Leaderboard

UGI Leaderboard data, Apache-2.0 · Updated Oct 16, 2026

UGI Score

37.4

#82 of 149

UGI Willingness

4.5

#55 of 149

UGI Writing

40.3

#89 of 149

Filtered and ranked to models on NanoGPT.

Providers

Auto routing is available for this model. Explicit provider selection is not available.

Auto
Auto
Recommended
$0.40$1.40$0.20N/AN/A
Batch API
ProviderInputOutputCached input
Auto
Automistralai/mistral-small-4-119b-2603:thinking
$0.40/M$1.40/M$0.20/M

Batch rows for this model use normal routing and cost the same as standard API requests. Set provider in a row to choose a provider.

Reliability

Related text models

Compare Mistral Small 4 119B Thinking with similar models from the same provider or model family.

Mistral Small 4 119B

mistralai/mistral-small-4-119b-2603

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.

Mistral Small 3 24B (2501)

mistralai/mistral-small-24b-instruct-2501

Mistral Small 3 24B (2501) hosted by IONOS in Berlin, Germany. Zero data retention.

Mistral Devstral Small 2505

mistralai/devstral-small-2505

OpenHands+Devstral is 100% local 100% open, and is SOTA for the category on SWE-Bench Verified: 46.8% accuracy.

Mistral Medium 3

mistralai/mistral-medium-3

Mistral Medium 3 delivers frontier performance while being an order of magnitude less expensive. For instance, the model performs at or above 90% of Claude Sonnet 3.7 on benchmarks across the board at a significantly lower cost. On performance, Mistral Medium 3 also surpasses leading open models such as Llama 4 Maverick and enterprise models such as Cohere Command A. On pricing, the model beats cost leaders such as DeepSeek v3, both in API and self-deployed systems.

Mistral Medium 3.1

mistralai/mistral-medium-3.1

Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost compared to traditional large models, making it suitable for scalable deployments across professional and industrial use cases. The model excels in domains such as coding, STEM reasoning, and enterprise adaptation. It supports hybrid, on-prem, and in-VPC deployments and is optimized for integration into custom workflows. Mistral Medium 3.1 offers competitive accuracy relative to larger models like Claude Sonnet 3.5/3.7, Llama 4 Maverick, and Command R+, while maintaining broad compatibility across deployment environments.

Mistral Large 2411

mistralai/mistral-large

Upgrade to Mistral's flagship model. It is fluent in English, French, Spanish, German, and Italian, with high grammatical accuracy, with a long context window.