Mistral Large 4 vs Claude Haiku 5.5

Overall
28
vs
Overall
70

Claude Haiku 5.5 is clearly better. It wins 74 of the 76 test cases where they differ.

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Task by task

A score turns orange only when that model wins clearly more of the task's test cases. Under each score, the average time per test case on the machine it ran on. Mistral Large 4 spends 1.5× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
281m 56s
6.2K, 72% thinking3.9K, 78% thinking
7025.5s
Agents
1126.1s
795, no thinking3.7K, 61% thinking
6139.5s
Structured Extraction
153.78s
288, no thinking2.6K, 83% thinking
9013.5s
Coding
332m 48s
9.3K, 37% thinking6.8K, 76% thinking
8630.6s
Grounded Answers
382m 45s
8.1K, 89% thinking2.2K, 78% thinking
7613.9s
Instruction Following
693m 47s
12.9K, 84% thinking4.3K, 82% thinking
9431.5s
Business Logic
242m 40s
8.8K, 77% thinking5.5K, 95% thinking
6726.0s
Security & permissions
331m 9s
3.7K, 83% thinking2.7K, 70% thinking
6723.4s
Diagnosis & investigation
01m 19s
4.4K, 85% thinking2.3K, 50% thinking
1725.5s

What you'd run

The build behind each score. Orange marks the faster, smaller, cheaper or longer-context side.

SpecAB
Speed
56 tok/s
225 tok/s (better)
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
512K
1M (better)
Cost per run
$2.67
$0.42 (better)
Cost per case
$0.017
$0.0028 (better)
Time per case
1m 56s
25.5s (better)
Quantization
—
—
Harness
openrouter
openrouter

The race

No lead changes

Each model's running score as the test cases go by. The dashed line is a perfect run.

Mistral Large 4Claude Haiku 5.5
025507510050100150Perfect run2870

Every test case

153 test cases

Each square is one test case, colored by the model that scored higher.

2 won by Mistral Large 474 won by Claude Haiku 5.577 tied