LLM Comparison

Claude Sonnet 5.5 vs Mistral Large 4: benchmark scores, pricing & comparison.

Side-by-side Claude Sonnet 5.5 vs Mistral Large 4 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Verdict: Claude Sonnet 5.5 ranks higher (#4 vs #30) and wins 3 of 3 shared benchmarks; Mistral Large 4 costs less ($0.68/$2.09 vs $2.00/$10.0 per 1M tokens).

Rank #4 vs #30AskClash overall scores 76.8 vs 52.5.
Pricing $2.00/$10.0 vs $0.68/$2.09Input and output token prices per 1M tokens when published.
Proprietary vs PendingAnthropic vs Mistral.

Claude Sonnet 5.5 vs Mistral Large 4 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricClaude Sonnet 5.5Mistral Large 4
Overall Score76.852.5
Leaderboard Rank#4#30
ACB76.6—
HLE64.535.0
SWE-Pro81.3—
Terminal-Bench63.6—
DeepSWE71.0—
GDPval-AA1844.21423.9
Finance Agent58.154.7
MMMU-Pro—76.4
Input Price (per 1M tokens)$2.00$0.68
Output Price (per 1M tokens)$10.0$2.09
Context Window1M1M
Benchmarks Published107

Claude Sonnet 5.5 vs Mistral Large 4 head-to-head charts

Claude Sonnet 5.5 leads 4 and Mistral Large 4 leads 0 of 4 shared benchmarks. Mistral Large 4 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Sonnet 5.5Mistral Large 4
Overall
76.8Claude Sonnet 5.5
52.5Mistral Large 4
HLE
64.5Claude Sonnet 5.5
35.0Mistral Large 4
GDPval-AA
1844.2Claude Sonnet 5.5
1423.9Mistral Large 4
Finance Agent
58.1Claude Sonnet 5.5
54.7Mistral Large 4
Claude Sonnet 5.5
Input$2.00
Output$10.0
Workload$4.00
Context1M
Mistral Large 4
Input$0.68
Output$2.09
Workload$1.10
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Claude Sonnet 5.5 and Mistral Large 4 comparisons

Explore how Claude Sonnet 5.5 and Mistral Large 4 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.