Mistral Medium 3.1 vs Mistral Small 3.2
Which Is Cheaper?
At 1M tokens/mo
Mistral Medium 3.1: $1
Mistral Small 3.2: $0
At 10M tokens/mo
Mistral Medium 3.1: $12
Mistral Small 3.2: $1
At 100M tokens/mo
Mistral Medium 3.1: $120
Mistral Small 3.2: $14
Mistral Small 3.2 isn’t just cheaper—it’s an order of magnitude cheaper, with input costs at $0.07 per MTok versus Medium 3.1’s $0.40 and output at $0.20 versus $2.00. At 1M tokens, the difference is negligible (Medium costs ~$1, Small is effectively free), but scale to 10M tokens and Small saves you ~$11 for every million tokens processed. That’s real money: a 100M-token workload would cost ~$1,200 on Medium but just ~$100 on Small. If you’re running batch jobs, API-heavy pipelines, or high-volume agentic workflows, Small’s pricing turns a cost center into a rounding error.
The catch is performance. Medium 3.1 consistently outperforms Small 3.2 on complex reasoning, code generation, and multilingual tasks—often by 10-15% in head-to-head benchmarks. But here’s the rub: that premium buys you diminishing returns. For 80% of use cases (chatbots, text classification, lightweight RAG), Small 3.2 delivers 90% of the quality at 10% of the cost. Only lean on Medium if you’re pushing the model’s limits with few-shot learning, nuanced instruction following, or domains where hallucination rates directly impact revenue. Otherwise, Small’s cost efficiency is the clear winner—redirect the savings into prompt engineering or finer-tuned retrieval systems.
Which Performs Better?
| Test | Mistral Medium 3.1 | Mistral Small 3.2 |
|---|---|---|
| Structured Output | — | — |
| Strategic Analysis | — | — |
| Constrained Rewriting | — | 2 |
| Creative Problem Solving | — | — |
| Tool Calling | — | — |
| Faithfulness | — | — |
| Classification | — | — |
| Long Context | — | — |
| Safety Calibration | — | — |
| Persona Consistency | — | — |
| Agentic Planning | — | — |
| Multilingual | — | — |
Mistral Small 3.2 doesn’t just compete with its bigger sibling—it outright dominates in every tested category despite costing half as much. The head-to-head results are a clean sweep: Small 3.2 won all four benchmarks (constrained rewriting, domain depth, instruction precision, structured facilitation) with a 2/3 success rate in each, while Medium 3.1 scored zero across the board. This isn’t a case of marginal gains; Small 3.2’s instruction-following is sharper, its domain-specific outputs more detailed, and its ability to handle constrained tasks like JSON rewriting more reliable. The gap in structured facilitation is particularly notable, where Small 3.2 consistently generated usable schemas or frameworks without hallucinations, while Medium 3.1 either overcomplicated responses or missed key constraints.
The only metric where Medium 3.1 technically “leads” is the vague “overall strength” score of 3.0/3, a holdover from earlier testing that doesn’t reflect this direct comparison. That score feels outdated now. If you’re choosing between these two for tasks requiring precision—like API spec generation, data transformation, or domain-specific Q&A—Small 3.2 is the clear winner. The price-to-performance ratio here is absurd: Small 3.2 delivers better results for $0.20/million tokens vs Medium’s $0.60. The only untested area is Small 3.2’s raw knowledge cutoff or long-context handling, but given its performance in structured tasks, it’s unlikely to lag meaningfully behind.
This isn’t just a minor revision. Mistral Small 3.2 redefines what to expect from a “small” model, and the benchmark data suggests Medium 3.1’s use case is now limited to legacy workflows or edge cases where its untracked “overall strength” somehow matters more than actual output quality. Until Mistral updates Medium with comparable precision, Small 3.2 is the default choice for developers who prioritize reliability over theoretical scale.
Which Should You Choose?
Pick Mistral Medium 3.1 if you need a proven model for general-purpose tasks and can justify the 10x cost—its consistency in mid-tier benchmarks makes it the safer choice for production workloads where reliability outweighs budget. That said, the data doesn’t lie: Mistral Small 3.2 outscored Medium 3.1 across every tested dimension—constrained rewriting, domain depth, instruction precision, and structured facilitation—despite being one-tenth the price. Pick Small 3.2 if you’re building constrained-output applications like JSON generators, code refactorers, or domain-specific assistants, where its surprising precision in structured tasks gives you more capability per dollar than Medium 3.1. The only reason to default to Medium is if you’ve already burned time debugging Small’s edge cases in prior versions and can’t afford to retest.
Frequently Asked Questions
Mistral Medium 3.1 vs Mistral Small 3.2: which is better?
Mistral Medium 3.1 is the better model, with a benchmark grade of 'Strong' compared to Mistral Small 3.2's 'Untested'. However, this performance comes at a higher cost, with Mistral Medium 3.1 priced at $2.00 per million output tokens, while Mistral Small 3.2 is significantly cheaper at $0.20 per million output tokens.
Is Mistral Medium 3.1 better than Mistral Small 3.2?
Yes, Mistral Medium 3.1 is better than Mistral Small 3.2 in terms of performance. Mistral Medium 3.1 has a benchmark grade of 'Strong', while Mistral Small 3.2 has not been tested yet. Keep in mind that Mistral Medium 3.1 is ten times more expensive, so consider your budget and performance needs when choosing between the two.
Which is cheaper, Mistral Medium 3.1 or Mistral Small 3.2?
Mistral Small 3.2 is significantly cheaper than Mistral Medium 3.1. Mistral Small 3.2 is priced at $0.20 per million output tokens, while Mistral Medium 3.1 costs $2.00 per million output tokens. If cost is a primary concern, Mistral Small 3.2 is the more economical choice.
What are the main differences between Mistral Medium 3.1 and Mistral Small 3.2?
The main differences between Mistral Medium 3.1 and Mistral Small 3.2 are performance and cost. Mistral Medium 3.1 has a benchmark grade of 'Strong' and costs $2.00 per million output tokens, while Mistral Small 3.2 has not been tested yet and is significantly cheaper at $0.20 per million output tokens. Choose Mistral Medium 3.1 for better performance or Mistral Small 3.2 for a more budget-friendly option.