Standard Compute
Model comparison 2026

Claude Sonnet 5.5 vs Mistral Large 4

Claude Sonnet 5.5
Anthropic · Balanced · Proprietary
$4.40/1M · 1M ctx
Mistral Large 4
Mistral · Balanced · Open weights
$1.10/1M · 1.0M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality
Correctness and depth of what it produces
Agentic Ability
Tool calls, instruction-following, and multi-step tasks
Speed
Tokens per second and time-to-first-token
Value for money
How much capability you get per dollar
Reliability
Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
Sonnet 5.5
Mistral Large 4
Maker
Anthropic
Mistral
Blended price / 1M
$4.40
$1.10
Input / output
$2.00 in · $10 out / 1M tokens
$0.68 in · $2.09 out / 1M tokens
Context window
1M
1.0M
Open weights
No
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
9.8
7.6
Agentic Ability
9.7
7.1
Speed
8.4
7.0
Value for money
6.7
5.9
Reliability
9.4
8.8

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: Sonnet 5.5 or Mistral Large 4?

Updated 2026-10-13

Choose Claude Sonnet 5.5 if you want the everyday default for coding agents, escalating to Opus 5.5 for the hardest tasks. Choose Mistral Large 4 if you want open-weight, EU-provenance agent work that needs long context and image input.

In our editorial scoring, Claude Sonnet 5.5 leads in 5 of five dimensions (output quality, agentic ability, speed, value for money and reliability), while Mistral Large 4 leads in 0. On price, Claude Sonnet 5.5 runs about $4.40 per 1M tokens (blended) and is proprietary; Mistral Large 4 is about $1.10 and open-weight.

Where Sonnet 5.5 falls short
  • Artificial Analysis flags it as very verbose, which adds output tokens
  • A cache miss bills input at $2 per million, 20 times the cache-read rate
Full Sonnet 5.5 breakdown →
Where Mistral Large 4 falls short
  • Still a public preview, so behavior and price can change
  • 26.8% in Artificial Analysis's Terminal-Bench 4.0 run, well below the frontier models
Full Mistral Large 4 breakdown →

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