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Mistral Large 4 vs Qwen3.8-27B

Mistral Large 4 and Qwen3.8-27B are closely matched at 46.2 and 44.6 on the LLM Stats Score. Mistral Large 4 is 1.0x cheaper per token.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Mistral Large 4 and Qwen3.8-27B are closely matched on the overall LLM Stats Score at 46.2 and 44.6.

In the 1 individual benchmarks reported for both models, Mistral Large 4 wins 1; this is a narrower head-to-head signal than the composite indexes.

Mistral Large 4 also accepts a larger context window (1,000,000 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 Mistral Large 4

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen3.8-27B

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Mistral Large 4
Mistral AI
Qwen3.8-27B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
46.2
#34
44.6
#43
Reasoning
44.4
#38
44.3
#40
Coding
35.4
#27
30.2
#54
Agents
34.0
#26
29.5
#45
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.68 / M
$0.40 / M
Output price
$2.09 / M
$3.00 / M
Context window
1,000,000
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Mistral Large 4
Qwen3.8-27B
Vision
1.1#189
32.9#21
Tool use
29.1#17
20.2#59
Multimodal
1.7#162
36.6#9
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

18 reported for Mistral Large 4 · 26 for Qwen3.8-27B

1 shared

Mistral Large 4 outperforms in 1 benchmarks (DeepSWE 1.1), while Qwen3.8-27B is better at 0 benchmarks.

Mistral Large 4 significantly outperforms across most benchmarks.

Wed Oct 14 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Mistral Large 4 costs less

For input processing, Mistral Large 4 ($0.68/1M tokens) is 1.7x more expensive than Qwen3.8-27B ($0.40/1M tokens).

For output processing, Mistral Large 4 ($2.09/1M tokens) is 1.4x cheaper than Qwen3.8-27B ($3.00/1M tokens).

In conclusion, Qwen3.8-27B is more expensive than Mistral Large 4.*

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

Lowest available price from all providers
Wed Oct 14 2026 • llm-stats.com
Mistral AI
Mistral Large 4
Input tokens$0.68
Output tokens$2.09
Best providerMistral
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input tokens$0.40
Output tokens$3.00
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

1022.2B diff

Mistral Large 4 has 1022.2B more parameters than Qwen3.8-27B, making it 3679.5% larger.

Mistral AI
Mistral Large 4
1.1Tparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
1050.0B
Mistral Large 4
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

Mistral Large 4 accepts 1,000,000 input tokens compared to Qwen3.8-27B's 262,144 tokens. Only Qwen3.8-27B specifies output context (262,144 tokens).

Mistral AI
Mistral Large 4
Input1,000,000 tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input262,144 tokens
Output262,144 tokens
Wed Oct 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Mistral Large 4 and Qwen3.8-27B support multimodal inputs.

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

Mistral Large 4

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

Mistral Large 4 is licensed under a proprietary license, while Qwen3.8-27B uses Apache 2.0.

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

Mistral Large 4

Proprietary

Closed source

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mistral Large 4 was released on 2026-10-06, while Qwen3.8-27B was released on 2026-08-14.

Mistral Large 4 is 2 months newer than Qwen3.8-27B.

Mistral Large 4

Oct 6, 2026

5 days ago

1mo newer
Qwen3.8-27B

Aug 14, 2026

1 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

Mistral Large 4 is available from Mistral AI. Qwen3.8-27B is available from DeepInfra, FriendliAI.

Mistral Large 4

mistral logo
Mistral
Input Price:Input: $0.68/1MOutput Price:Output: $2.09/1M

Qwen3.8-27B

deepinfra logo
Deepinfra
Input Price:Input: $0.40/1MOutput Price:Output: $3.00/1M
friendli logo
FriendliAI
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Mistral Large 4 and Qwen3.8-27B side-by-side, then vote on the output you prefer.

Mistral Large 4
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about Mistral Large 4 vs Qwen3.8-27B.

Which is better, Mistral Large 4 or Qwen3.8-27B?

Mistral Large 4 and Qwen3.8-27B are closely matched on the LLM Stats Score at 46.2 and 44.6. Mistral Large 4 is made by Mistral AI and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Mistral Large 4 compare to Qwen3.8-27B in benchmarks?

Mistral Large 4 scores B3 AI Security Benchmark: 93.3%, CyBench: 93.0%, SciCode: 91.8%, KORABench: 84.5%, CyberGym: 82.0%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

Is Mistral Large 4 cheaper than Qwen3.8-27B?

Qwen3.8-27B is 1.7x cheaper for input tokens. Mistral Large 4 costs $0.68/M input and $2.09/M output via mistral. Qwen3.8-27B costs $0.40/M input and $3.00/M output via deepinfra.

What are the context window sizes for Mistral Large 4 and Qwen3.8-27B?

Mistral Large 4 supports 1.0M tokens and Qwen3.8-27B supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Mistral Large 4 and Qwen3.8-27B?

Key differences include LLM Stats Score (46.2 vs 44.6), context window (1.0M vs 262K), input pricing ($0.68 vs $0.40/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral Large 4 and Qwen3.8-27B?

Mistral Large 4 is developed by Mistral AI and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.

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