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DeepSeek-V4.1-Flash-1017 vs Pixtral-12B

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -1.9. Pixtral-12B is 3.5x 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 -1.9, ranking #15 overall.

On price, Pixtral-12B is roughly 3.5x 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 and coding — it leads those capability indexes
  • 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-12B

  • cost matters — it's about 3.5x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Pixtral-12B
Mistral AI
Core performance indexes
LLM Stats Score
51.0
#15
-1.9
#360
Reasoning
48.6
#18
-4.0
#362
Coding
39.1
#15
-2.7
#273
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.15 / M
Output price
$1.20 / M
$0.15 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V4.1-Flash-1017
Pixtral-12B
Math
31.8#67
1.0#307
Vision
32.2#26
0.0#200
Multimodal
35.0#14
3.7#159
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 12 for Pixtral-12B

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Pixtral-12Bdon'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

Pixtral-12B costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 2.0x more expensive than Pixtral-12B ($0.15/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 8.0x more expensive than Pixtral-12B ($0.15/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Pixtral-12B.*

* 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-12B
Input tokens$0.15
Output tokens$0.15
Best providerMistral
Notice missing or incorrect data?

Model Size

Parameter count comparison

750.8B diff

DeepSeek-V4.1-Flash-1017 has 750.8B more parameters than Pixtral-12B, making it 6054.9% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Mistral AI
Pixtral-12B
12.4Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
12.4B
Pixtral-12B

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Pixtral-12B's 128,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Pixtral-12B is limited to 8,192 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Mistral AI
Pixtral-12B
Input128,000 tokens
Output8,192 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Pixtral-12B 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-12B

Text
Images
Audio
Video

License

Usage and distribution terms

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

MIT

Open weights

Pixtral-12B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Pixtral-12B was released on 2024-09-17.

DeepSeek-V4.1-Flash-1017 is 25 months newer than Pixtral-12B.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

2.1yr newer
Pixtral-12B

Sep 17, 2024

2.1 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-12B 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-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?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Pixtral-12B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Pixtral-12B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Pixtral-12B.

Which is better, DeepSeek-V4.1-Flash-1017 or Pixtral-12B?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -1.9. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Pixtral-12B 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-12B 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-12B scores DocVQA: 90.7%, ChartQA: 81.8%, VQAv2: 78.6%, MT-Bench: 76.8%, HumanEval: 72.0%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Pixtral-12B?

Pixtral-12B is 2.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Pixtral-12B costs $0.15/M input and $0.15/M output via mistral.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Pixtral-12B?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Pixtral-12B 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-12B?

Key differences include LLM Stats Score (51.0 vs -1.9), context window (1.0M vs 128K), input pricing ($0.30 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Pixtral-12B?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Pixtral-12B is developed by Mistral AI.

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