One of the cheapest models in the directory at $0.10/1M input
Multimodal — handles images alongside text at this price point
Fast and efficient for simple, well-defined tasks
Weaknesses
Weak on complex reasoning, hard coding, and nuanced writing
Not suitable for tasks requiring deep context retention or multi-step logic
Limited to simpler use cases compared to Codestral or DeepSeek V3
Real-world use cases
What people actually use Mistral Small 3.1 for.
Bulk document classification and tagging pipelines at near-zero cost
Image description and OCR-adjacent tasks where full multimodal models are overkill
High-frequency lightweight summarisation in cost-sensitive products
How Mistral Small 3.1 compares
The nearest models people weigh against it, and what actually separates them.
vs Mistral Medium 3.5 — Against Mistral Medium 3.5 (Mistral), Mistral Small 3.1 runs about 96% cheaper per token, gives up 2x on context and answers faster. Take Mistral Small 3.1 unless you specifically need what Mistral Medium 3.5 does better.
vs GPT-6 Astra — Against GPT-6 Astra (OpenAI), Mistral Small 3.1 runs about 99% cheaper per token, gives up 8.2x on context and answers faster. Take Mistral Small 3.1 unless you specifically need what GPT-6 Astra does better.
vs GPT-5.2 Mini — Against GPT-5.2 Mini (OpenAI), Mistral Small 3.1 runs about 93% cheaper per token and answers faster. Take Mistral Small 3.1 unless you specifically need what GPT-5.2 Mini does better.
Price History
Mistral Small 3.1 pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
Ready to try it?
Start using Mistral Small 3.1
Ultra-high-volume classification, summarisation, and lightweight vision tasks. Start free — no card required.
A 128B dense open-weight multimodal model handling reasoning, coding, and vision in one set of weights — frontier-adjacent coding at mid-tier prices, self-hostable under a modified MIT license.
Verdict
Best self-hostable multimodal model — European, dense, MIT-licensed.
Quality score
84%
Pricing
$1.50/1M in
$7.50/1M out
Speed
Balanced
3/5 speed
Context
256k tokens
Released April 29, 2026 (model ID mistral-medium-3-5-26-04). Pricing verified on docs.mistral.ai. Le Chat Pro $14.99/mo does not include API usage.
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
Verdict
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Quality score
99%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1.1M tokens
Released September 3, 2026. API ID gpt-6-astra; rolling out over the coming days to ChatGPT Plus, Pro, Business and Enterprise (usage inside existing allowances; GPT-6 Astra Pro for Pro/Business/Enterprise; Enterprise off by default), the OpenAI API, Microsoft Azure and Amazon Bedrock. Standard API pricing $10/$50 per 1M tokens; Fast mode is up to 2x speed at 2x price; cache reads and writes have separate rates. Model docs list 1,050,000 context, 128,000 max output, knowledge cutoff April 30, 2026, reasoning efforts up to 'max'. Published launch numbers (Astra / GPT-5.6 Sol / Fable 5.1 / Opus 5): OSWorld 2.0 72.6 / 65.7 / — / 70.2; Terminal-Bench 4.0 57.9 / 37.3 / 55.8 / 52.3; Terminal-Bench Science 0.1 64.6 / 22.4 / 52.6 / 30.0; FrontierMath Tier 4 v2 97.6 / 83.0 / 87.8 / 73.2; GPQA Diamond 96.0 / 94.6 / 93.7 / 93.7; Humanity's Last Exam w/ tools 57.2 / — / 65.0 / 63.6; AutomationBench 41.4 / 18.1 / 31.4 / 26.9; DeepSWE v1.1 74.1 / 72.7 / 67.4 / 73.7; ARC-AGI-2 95.0 / 92.5 / 90.0 / 90.4; ARC-AGI-3 99.9 (OpenAI responses-API harness; ARC Prize's stateless runs score far lower) / 7.8 / — / 30.2; ExploitBench 100.0 / 78.5 / — / 70; SRE-Bench 88.0 / 55.9; Artificial Analysis Intelligence Index v4.1.1 61.2 / 60.9 / 65.7 / 63.1. Meets the Critical threshold for cybersecurity under OpenAI's Preparedness Framework; advanced cyber workflows gated behind OpenAI Daybreak. All figures from OpenAI's launch post and model docs, verified September 4, 2026.
Computer use leaderFrontierAgenticReasoningLong contextPremiumNew
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
Mistral Small 3.1 costs $0.1 per million input tokens and $0.3 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $1.60 at list price, before any batch or caching discounts.
What is Mistral Small 3.1 best for?
Mistral Small 3.1 is best for ultra-high-volume classification, summarisation, and lightweight vision tasks. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
When should I avoid Mistral Small 3.1?
You need reliable multi-step reasoning or coding quality — it won't hold up.
What is a cheaper alternative to Mistral Small 3.1?
GPT-5.6 Terra (OpenAI) at $2.00/1M/1M input against Mistral Small 3.1's $0.10/1M/1M. Best OpenAI value — near-flagship capability at 60% off. Compare it first if Mistral Small 3.1's pricing is the thing stopping you.
What is a faster alternative to Mistral Small 3.1?
Mistral Medium 3.5 — balanced against Mistral Small 3.1's very fast, with 256k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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