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DeepSeek-V4.1-Flash-1017 vs Pixtral Large

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 11.5. DeepSeek-V4.1-Flash-1017 is 5.7x cheaper per token.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 11.5, ranking #15 overall.

On price, DeepSeek-V4.1-Flash-1017 is roughly 5.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • cost matters — it's about 5.7x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose Pixtral Large

  • you want predictable pricing at $2.00/M input and $6.00/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Pixtral Large
Mistral AI
Core performance indexes
LLM Stats Score
51.0
#15
11.5
#280
Reasoning
48.6
#18
12.8
#264
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$2.00 / M
Output price
$1.20 / M
$6.00 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
Pixtral Large
Vision
32.2#26
10.8#132
Multimodal
35.0#14
13.2#118
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 7 for Pixtral Large

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Pixtral Largedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4.1-Flash-1017 costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 6.7x cheaper than Pixtral Large ($2.00/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 5.0x cheaper than Pixtral Large ($6.00/1M tokens).

In conclusion, Pixtral Large is more expensive than DeepSeek-V4.1-Flash-1017.*

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

Lowest available price from all providers
Tue Oct 20 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Mistral AI
Pixtral Large
Input tokens$2.00
Output tokens$6.00
Best providerMistral
Notice missing or incorrect data?

Model Size

Parameter count comparison

639.2B diff

DeepSeek-V4.1-Flash-1017 has 639.2B more parameters than Pixtral Large, making it 515.5% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Pixtral Large's 128,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Pixtral Large is limited to 128,000 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Pixtral Large support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017

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-V4.1-Flash-1017 was released on 2026-10-17, while Pixtral Large was released on 2024-11-18.

DeepSeek-V4.1-Flash-1017 is 23 months newer than Pixtral Large.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1.9yr newer
Pixtral Large

Nov 18, 2024

1.9 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-V4.1-Flash-1017 is available from DeepSeek. Pixtral Large is available from Mistral AI.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Pixtral Large

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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Pixtral Large side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Pixtral Large
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Pixtral Large.

Which is better, DeepSeek-V4.1-Flash-1017 or Pixtral Large?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 11.5. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Pixtral Large is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash-1017 compare to Pixtral Large in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Pixtral Large?

DeepSeek-V4.1-Flash-1017 is 6.7x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Pixtral Large costs $2.00/M input and $6.00/M output via mistral.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Pixtral Large?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Pixtral Large supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash-1017 and Pixtral Large?

Key differences include LLM Stats Score (51.0 vs 11.5), context window (1.0M vs 128K), input pricing ($0.30 vs $2.00/M), 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.

Who makes DeepSeek-V4.1-Flash-1017 and Pixtral Large?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Pixtral Large is developed by Mistral AI.

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