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Van Data Team

text model comparison

Claude Opus 5.5 vs Mistral Large 4

Claude Opus 5.5 and Mistral Large 4 are both current text models, from Anthropic and Mistral AI. Mistral Large 4 is 83% cheaper per 1M input tokens than Claude Opus 5.5, $0.70 vs $4. On Arena Text, Claude Opus 5.5 scores 1509 Elo and Mistral Large 4 1432 Elo (Arena, measured October 28, 2026). Both accept 1,000,000 tokens of context.

Higher Arena Text
Claude Opus 5.51509 Elo against 1432 Elo
Lower price per 1M input tokens
Mistral Large 4$0.70 against $4
Newer release
Mistral Large 4Oct 2026 against Sep 2026

Data verified November 3, 2026 · Dataset 2026-11-03

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Side by side

Claude Opus 5.5 and Mistral Large 4, line by line

Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.

FactClaude Opus 5.5Mistral Large 4
Price
Price per 1M input tokens$4$0.70 (better)
Price per 1M output tokens$20$2.10 (better)
Independent benchmarks
Arena Text1509 Elo (#2 of 51) (better)1432 Elo (#40 of 51)
Arena WebDev1810 Elo (#1 of 45) (better)1544 Elo (#32 of 45)
FrontierMath Tiers 1-3 (v2)91.2% (#3 of 42) (better)46.3% (#36 of 42)
GPQA Diamond90.6% (#25 of 41) (better)90.2% (#28 of 41)
SimpleQA Verified72.2% (#5 of 38) (better)22.4% (#36 of 38)
Specs
ProviderAnthropicMistral AI
Release dateSeptember 22, 2026October 6, 2026
AccessAPI onlyAPI and open weights
Context window1,000,000 tokens1,000,000 tokens
Max output128,000 tokensNot reported
Inputtext, imagetext, image
Outputtexttext

Scores:Arena · 2026-11-03Epoch AI · 2026-11-03

Open both in the interactive comparison

Charts

Against every current text model

Where Claude Opus 5.5 and Mistral Large 4 land among the current models of their task, on every independent benchmark, on price and on context.

Where each stands

On Arena Text, Claude Opus 5.5 ranks #2 and Mistral Large 4 #40 of 51 current models. Each bar is the share of current models it beats: on score, price and context.

Claude Opus 5.5 and Mistral Large 4 among the current text models, one row per benchmark, price and context window.

Independent benchmarks

Arena Text

Claude Opus 5.5:#2of 51

1,509 Elo · ahead of 98%

Mistral Large 4:#40of 51

1,432 Elo · ahead of 22%

Arena WebDev

Claude Opus 5.5:#1of 45

1,810 Elo · ahead of 100%

Mistral Large 4:#32of 45

1,544 Elo · ahead of 30%

FrontierMath Tiers 1-3 (v2)

Claude Opus 5.5:#3of 42

91.2% · ahead of 95%

Mistral Large 4:#36of 42

46.3% · ahead of 15%

GPQA Diamond

Claude Opus 5.5:#25of 41

90.6% · ahead of 40%

Mistral Large 4:#28of 41

90.2% · ahead of 30%

SimpleQA Verified

Claude Opus 5.5:#5of 38

72.2% · ahead of 89%

Mistral Large 4:#36of 38

22.4% · ahead of 5%

Price and context

Price per 1M input tokens

Claude Opus 5.5:#43of 52

$4 · cheaper than 14%

Mistral Large 4:#19of 52

$0.70 · cheaper than 65%

Price per 1M output tokens

Claude Opus 5.5:#43of 52

$20 · cheaper than 14%

Mistral Large 4:#16of 52

$2.10 · cheaper than 71%

Context window

Claude Opus 5.5:#26of 64

1M tokens · longer than 22%

Mistral Large 4:#26of 64

1M tokens · longer than 22%

Scores fromArena · 2026-11-03Epoch AI · 2026-11-03

Quality against price

Arena Text · measured October 28, 2026

Claude Opus 5.5 scores 1,509 at $8; Mistral Large 4 scores 1,432 at $1.05 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.

Quality against priceArena Text score against price for 43 text models, Claude Opus 5.5 and Mistral Large 4 marked.1,2501,3001,3501,4001,4501,5001,550$0.30$1$3$10MOST ATTRACTIVE QUADRANTMedian price $3Median 1,475Blended price per 1M tokens (3 input : 1 output), log scaleArena Text (Elo)Claude Opus 5.5Mistral Large 4
Quality against price: the data
Arena Text score against price for 43 text models, Claude Opus 5.5 and Mistral Large 4 marked.
ModelProviderBlended price per 1M tokensArena Text (Elo)
Gemini 4 ArgonGoogle$41,520
Claude Opus 5.5Anthropic$81,509
Muse WonderMeta$81,507
Claude Fable 5Anthropic$201,504
Claude Fable 5.1Anthropic$201,504
Gemini 3.8 FlashGoogle$1.501,496
Muse Spark 1.3Meta$21,495
Claude Opus 5Anthropic$101,492
Kimi K3Moonshot Kimi$61,488
GPT-5.6 SolOpenAI$81,485
Gemini 3.6 FlashGoogle$31,483
GPT-5.5OpenAI$111,482
Claude Opus 4.8Anthropic$101,482
Qwen3.8-MaxAlibaba Qwen$31,482
GPT-6.1 SolOpenAI$41,481
GLM-5.3Z.ai$2.151,481
MiMo-V2.6-ProXiaomi MiMo$0.541,480
Claude Sonnet 5.5Anthropic$41,477
GLM-5.3-FlashZ.ai$0.241,477
GPT-6 AstraOpenAI$201,476
DeepSeek-V4.1-FlashDeepSeek$0.521,476
GPT-5.4OpenAI$5.631,475
Gemini 3 Flash PreviewGoogle$1.131,473
Grok 4.20xAI$1.561,472
GPT-5.6 TerraOpenAI$4.501,467
Grok 4.5xAI$31,465
DeepSeek-V4-ProDeepSeek$1.981,465
Claude Sonnet 5Anthropic$41,462
GPT-6 SolOpenAI$41,458
Gemini 3.5 Flash-LiteGoogle$0.851,456
Grok 4.6xAI$31,455
GPT-5.6 LunaOpenAI$0.451,453
MiMo-V2.6-FlashXiaomi MiMo$0.181,448
Step 5 PreviewStepFun$1.431,448
Grok 4.3xAI$1.561,442
GPT-6 LunaOpenAI$0.201,441
Grok 4.7xAI$31,441
Mistral Large 4Mistral AI$1.051,432
Claude Haiku 5.5Anthropic$0.201,425
GPT-4.1OpenAI$3.501,415
Solar Pro 4Upstage$0.521,388
GPT-4.1 miniOpenAI$0.701,383
GPT-4.1 nanoOpenAI$0.181,322

Cost

What each costs

Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.

The same work, priced

For 10M input and 2M output tokens, Claude Opus 5.5 costs 7.1 times as much as Mistral Large 4, at each provider's listed rates.

What Claude Opus 5.5 and Mistral Large 4 cost for the same work, at the rates each provider lists.

  • 10M input and 2M output tokens

    Claude Opus 5.5 costs 7.1× as much

    Claude Opus 5.5
    $80
    Mistral Large 4
    $11.20

  • The same, with 9M of the input tokens cached

    Claude Opus 5.5 costs 8.3× as much

    Claude Opus 5.5
    $45.80
    Mistral Large 4
    $5.53
Workload or rateClaude Opus 5.5Mistral Large 4
Example workloads
10M input and 2M output tokens$80$11.20 (better)
The same, with 9M of the input tokens cached$45.80$5.53 (better)
The same, through the batch API$40Not listed
Other listed rates
1M input tokens, cached$0.20$0.07 (better)
1M input tokens, 5-minute cache write$5Not listed
1M input tokens, 1-hour cache write$8Not listed
1M input tokens, batch$2Not listed
1M output tokens, batch$10Not listed

Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.

Launch price $100, regular price $150

Book the cost audit

Verdict

When to choose each

Claude Opus 5.5

Where it leads

  • Higher Arena Text score, 1509 Elo vs 1432 Elo
  • Higher Arena WebDev score, 1810 Elo vs 1544 Elo
  • Higher FrontierMath Tiers 1-3 (v2) score, 91.2% vs 46.3%
  • Higher GPQA Diamond score, 90.6% vs 90.2%
  • Higher SimpleQA Verified score, 72.2% vs 22.4%
  • Batch pricing, $2 input and $10 output per 1M tokens

Best for

  • Long-running agentic coding and knowledge work as the general-purpose default
  • Cache-heavy agent loops where the 0.05x read multiplier compounds

Watch out for

  • The API effort default is medium here, not high as on Claude Fable 5.1 and Claude Sonnet 5.5, so a like-for-like comparison has to set effort explicitly
  • The 4.7-generation tokenizer produces roughly 30% more tokens for the same text than Claude Sonnet 4.6 and earlier, so per-token rates do not compare directly across generations
Full Claude Opus 5.5 profile

Mistral Large 4

Where it leads

  • Lower input and output prices, $0.70 and $2.10 vs $4 and $20 per 1M tokens
  • Open weights you can run yourself
  • Cheaper cached input, $0.07 vs $0.20 per 1M tokens

Best for

  • Self-hosted or European data-residency deployments that want a frontier-scale multimodal model
  • Coding and security agents where open weights and a low API price both matter

Watch out for

  • The API model is still labelled a public preview, and the open weights are a further-trained build of the October 6 preview
  • Businesses that sell it as a hosted model service need a separate commercial licence from Mistral
  • Running the open weights moves cost to your own GPUs, which the token rates here do not represent
  • Epoch AI measured 22.4% on SimpleQA Verified for the open-weight build, low for its size, so check factual recall on your own questions
Full Mistral Large 4 profile

From benchmark to production

Building on Claude Opus 5.5 or Mistral Large 4?

Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.

AI Model Cost AuditLaunch price $100, regular price $150What the audit includes

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FAQ

Claude Opus 5.5 vs Mistral Large 4 FAQ

Which is cheaper, Claude Opus 5.5 or Mistral Large 4?

Mistral Large 4 is 83% cheaper per 1M input tokens than Claude Opus 5.5, $0.70 vs $4. For 10M input and 2M output tokens, Claude Opus 5.5 costs $80 and Mistral Large 4 $11.20 at standard rates.

Which is cheaper with prompt caching, Claude Opus 5.5 or Mistral Large 4?

Claude Opus 5.5 charges $0.20 per 1M cached input tokens, 95% below its standard input rate, and Mistral Large 4 $0.07, 90% below. With 9M of 10M input tokens cached and 2M output tokens, Claude Opus 5.5 costs $45.80 and Mistral Large 4 $5.53.

Which scores higher on independent benchmarks, Claude Opus 5.5 or Mistral Large 4?

Claude Opus 5.5 leads on Arena Text, 1509 Elo to 1432 Elo; Claude Opus 5.5 leads on Arena WebDev, 1810 Elo to 1544 Elo; Claude Opus 5.5 leads on FrontierMath Tiers 1-3 (v2), 91.2% to 46.3%. Scores are independent evaluations, not either vendor's launch figures.

Which has the larger context window, Claude Opus 5.5 or Mistral Large 4?

Both accept 1,000,000 tokens of context.

Can I run Claude Opus 5.5 or Mistral Large 4 myself?

Mistral Large 4 is released as open weights you can run yourself; Claude Opus 5.5 is available through its provider's API only.

Further reading

More on Claude Opus 5.5 and Mistral Large 4

Articles on Claude Opus 5.5 and Mistral Large 4

Related comparisons

Production evaluation

Choosing between Claude Opus 5.5 and Mistral Large 4?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty
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