Model Comparison

DeepSeek-V3.1 vs Pixtral-12B

Comparing DeepSeek-V3.1 and Pixtral-12B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.1 and Pixtral-12B don'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

Pixtral-12B costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 1.8x more expensive than Pixtral-12B ($0.15/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 6.7x more expensive than Pixtral-12B ($0.15/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than Pixtral-12B.*

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

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Mistral AI
Pixtral-12B
Input tokens$0.15
Output tokens$0.15
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

658.6B diff

DeepSeek-V3.1 has 658.6B more parameters than Pixtral-12B, making it 5311.3% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Mistral AI
Pixtral-12B
12.4Bparameters
671.0B
DeepSeek-V3.1
12.4B
Pixtral-12B

Context Window

Maximum input and output token capacity

DeepSeek-V3.1 accepts 163,840 input tokens compared to Pixtral-12B's 128,000 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Pixtral-12B is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Mistral AI
Pixtral-12B
Input128,000 tokens
Output8,192 tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Pixtral-12B supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.1

Text
Images
Audio
Video

Pixtral-12B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Pixtral-12B uses Apache 2.0.

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

DeepSeek-V3.1

MIT

Open weights

Pixtral-12B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Pixtral-12B was released on 2024-09-17.

DeepSeek-V3.1 is 4 months newer than Pixtral-12B.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

3mo newer
Pixtral-12B

Sep 17, 2024

1.6 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-V3.1 is available from DeepInfra, Novita. Pixtral-12B is available from Mistral AI.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Pixtral-12B

mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Mistral AI
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Mistral AI
Pixtral-12B

FAQ

Common questions about DeepSeek-V3.1 vs Pixtral-12B

DeepSeek-V3.1 (DeepSeek) and Pixtral-12B (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Pixtral-12B scores DocVQA: 90.7%, ChartQA: 81.8%, VQAv2: 78.6%, MT-Bench: 76.8%, HumanEval: 72.0%.
Pixtral-12B is 1.8x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Pixtral-12B costs $0.15/M input and $0.15/M output via mistral.
DeepSeek-V3.1 supports 164K tokens and Pixtral-12B 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 $0.15/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.1 is developed by DeepSeek and Pixtral-12B is developed by Mistral AI.