Model Comparison

DeepSeek-V3.1 vs Pixtral Large

Comparing DeepSeek-V3.1 and Pixtral Large 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 Large 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

DeepSeek-V3.1 costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 7.4x cheaper than Pixtral Large ($2.00/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 6.0x cheaper than Pixtral Large ($6.00/1M tokens).

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

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

Lowest available price from all providers
Sat Apr 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Mistral AI
Pixtral Large
Input tokens$2.00
Output tokens$6.00
Best providerMistral
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Model Size

Parameter count comparison

547.0B diff

DeepSeek-V3.1 has 547.0B more parameters than Pixtral Large, making it 441.1% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
671.0B
DeepSeek-V3.1
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Sat Apr 11 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Pixtral Large 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 Large

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

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

DeepSeek-V3.1

MIT

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Pixtral Large was released on 2024-11-18.

DeepSeek-V3.1 is 2 months newer than Pixtral Large.

DeepSeek-V3.1

Jan 10, 2025

1.2 years ago

1mo newer
Pixtral Large

Nov 18, 2024

1.4 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 Large 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 Large

mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

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

Detailed Comparison

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

FAQ

Common questions about DeepSeek-V3.1 vs Pixtral Large

DeepSeek-V3.1 (DeepSeek) and Pixtral Large (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 Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.
DeepSeek-V3.1 is 7.4x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Pixtral Large costs $2.00/M input and $6.00/M output via mistral.
DeepSeek-V3.1 supports 164K tokens and Pixtral Large 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 $2.00/M), multimodal support (no vs yes), licensing (MIT vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.1 is developed by DeepSeek and Pixtral Large is developed by Mistral AI.