Flint vs Mistral Large 4

Overall
21
vs
Overall
28

Mistral Large 4 is clearly better. It wins 29 of the 44 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. Flint spends 2.2× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
211m 17s
10.9K, 90% thinking6.2K, 72% thinking
281m 56s
Agents
1447.7s
4.8K, 85% thinking795, no thinking
1126.1s
Structured Extraction
291m 17s
10.9K, 87% thinking288, no thinking
153.78s
Coding
141m 19s
12K, 98% thinking9.3K, 37% thinking
332m 48s
Grounded Answers
2957.7s
8.7K, 93% thinking8.1K, 89% thinking
382m 45s
Instruction Following
352m 28s
22.2K, 93% thinking12.9K, 84% thinking
693m 47s
Business Logic
101m 20s
11.7K, 78% thinking8.8K, 77% thinking
242m 40s
Security & permissions
3552.6s
7.1K, 90% thinking3.7K, 83% thinking
331m 9s
Diagnosis & investigation
057.0s
7.3K, 99% thinking4.4K, 85% thinking
01m 19s

What you'd run

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

SpecAB
Speed
149 tok/s (better)
56 tok/s
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
256K
512K (better)
Cost per run
Not measured
$2.67
Cost per case
Not measured
$0.017
Time per case
1m 17s (better)
1m 56s
Quantization
BF16
—
Harness
openrouter
openrouter

The race

5 lead changes

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

FlintMistral Large 4
0255075100501001502128

Every test case

153 test cases

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

15 won by Flint29 won by Mistral Large 4109 tied