Model Comparison

DeepSeek-V3.2 (Thinking) vs Mistral SmallWhich is better in 2026?

Comparing DeepSeek-V3.2 (Thinking) and Mistral Small across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.2 (Thinking) vs Mistral Small — which is better?

DeepSeek-V3.2 (Thinking) (by DeepSeek) and Mistral Small (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3.2 (Thinking) also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3.2 (Thinking) if…

  • you process long inputs — it offers a 131,072 token context window
  • you want the most recent training data — it shipped Dec 2025

Choose Mistral Small if…

  • you want predictable pricing at $0.20/M input and $0.60/M output

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Thinking) and Mistral Smalldon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mistral Small costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 1.4x more expensive than Mistral Small ($0.20/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 1.4x cheaper than Mistral Small ($0.60/1M tokens).

In conclusion, DeepSeek-V3.2 (Thinking) is more expensive than Mistral Small.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jul 18 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Mistral AI
Mistral Small
Input tokens$0.20
Output tokens$0.60
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

663.0B diff

DeepSeek-V3.2 (Thinking) has 663.0B more parameters than Mistral Small, making it 3013.6% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Mistral AI
Mistral Small
22.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
22.0B
Mistral Small

Context Window

Maximum input and output token capacity

DeepSeek-V3.2 (Thinking) accepts 131,072 input tokens compared to Mistral Small's 32,768 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while Mistral Small is limited to 32,768 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Mistral AI
Mistral Small
Input32,768 tokens
Output32,768 tokens
Sat Jul 18 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Mistral Small uses Mistral Research License.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Mistral Small

Mistral Research License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Mistral Small was released on 2024-09-17.

DeepSeek-V3.2 (Thinking) is 15 months newer than Mistral Small.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

7 months ago

1.2yr newer
Mistral Small

Sep 17, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3.2 (Thinking) is available from DeepSeek. Mistral Small is available from Mistral AI.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Mistral Small

mistral logo
Mistral
Input Price:Input: $0.20/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Less expensive output tokens
Mistral AI
Less expensive input tokens

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and Mistral Small side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
Mistral Small
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
Mistral AI
Mistral Small

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Mistral Small.

Which is better, DeepSeek-V3.2 (Thinking) or Mistral Small?

DeepSeek-V3.2 (Thinking) (DeepSeek) and Mistral Small (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2 (Thinking) compare to Mistral Small in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%.

Is DeepSeek-V3.2 (Thinking) cheaper than Mistral Small?

Mistral Small is 1.4x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. Mistral Small costs $0.20/M input and $0.60/M output via mistral.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Mistral Small?

DeepSeek-V3.2 (Thinking) supports 131K tokens and Mistral Small supports 33K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Thinking) and Mistral Small?

Key differences include context window (131K vs 33K), input pricing ($0.28 vs $0.20/M), licensing (MIT vs Mistral Research License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Thinking) and Mistral Small?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and Mistral Small is developed by Mistral AI.

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