Model Comparison

DeepSeek-V3.2-Exp vs Devstral Small 1.1

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. Devstral Small 1.1 is 2.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V3.2-Exp outperforms in 1 benchmarks (SWE-Bench Verified), while Devstral Small 1.1 is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Devstral Small 1.1 costs less

For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 2.7x more expensive than Devstral Small 1.1 ($0.10/1M tokens).

For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 1.4x more expensive than Devstral Small 1.1 ($0.30/1M tokens).

In conclusion, DeepSeek-V3.2-Exp is more expensive than Devstral Small 1.1.*

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

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Mistral AI
Devstral Small 1.1
Input tokens$0.10
Output tokens$0.30
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

661.0B diff

DeepSeek-V3.2-Exp has 661.0B more parameters than Devstral Small 1.1, making it 2754.2% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Mistral AI
Devstral Small 1.1
24.0Bparameters
685.0B
DeepSeek-V3.2-Exp
24.0B
Devstral Small 1.1

Context Window

Maximum input and output token capacity

DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to Devstral Small 1.1's 128,000 tokens. Devstral Small 1.1 can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Mistral AI
Devstral Small 1.1
Input128,000 tokens
Output128,000 tokens
Fri May 01 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while Devstral Small 1.1 uses Apache 2.0.

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

DeepSeek-V3.2-Exp

MIT

Open weights

Devstral Small 1.1

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Devstral Small 1.1 was released on 2025-07-11.

DeepSeek-V3.2-Exp is 3 months newer than Devstral Small 1.1.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

2mo newer
Devstral Small 1.1

Jul 11, 2025

9 months 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-Exp is available from Novita. Devstral Small 1.1 is available from Mistral AI.

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M

Devstral Small 1.1

mistral logo
Mistral
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Higher SWE-Bench Verified score (67.8% vs 53.6%)
Mistral AI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Mistral AI
Devstral Small 1.1

FAQ

Common questions about DeepSeek-V3.2-Exp vs Devstral Small 1.1

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Devstral Small 1.1 is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Devstral Small 1.1 scores SWE-Bench Verified: 53.6%.
Devstral Small 1.1 is 2.7x cheaper for input tokens. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita. Devstral Small 1.1 costs $0.10/M input and $0.30/M output via mistral.
DeepSeek-V3.2-Exp supports 164K tokens and Devstral Small 1.1 supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 128K), input pricing ($0.27 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and Devstral Small 1.1 is developed by Mistral AI.