Flint vs Spark X2.6 4B

Overall
21
vs
Overall
15

Flint is clearly better. It wins 26 of the 40 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 1.4× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
211m 17s
10.9K, 90% thinking8.2K, 84% thinking
151m 3s
Agents
1447.7s
4.8K, 85% thinking11.5K, 97% thinking
141m 32s
Structured Extraction
291m 17s
10.9K, 87% thinking5.3K, 78% thinking
1039.5s
Coding
141m 19s
12K, 98% thinking9.1K, 48% thinking
41m 8s
Grounded Answers
2957.7s
8.7K, 93% thinking6.6K, 86% thinking
1050.2s
Instruction Following
352m 28s
22.2K, 93% thinking11.9K, 90% thinking
371m 29s
Business Logic
101m 20s
11.7K, 78% thinking4.9K, 86% thinking
1036.3s
Security & permissions
3552.6s
7.1K, 90% thinking7K, 94% thinking
3154.3s
Diagnosis & investigation
057.0s
7.3K, 99% thinking11.6K, 98% thinking
01m 30s

What you'd run

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

SpecAB
Speed
149 tok/s
136 tok/s
Machine
Hosted
RTX 5090, 32 GB
Memory at 32K
—
9.4 GB
Context
256K
605K (better)
Cost per run
Not measured
$1.61 est.
Cost per case
Not measured
$0.011 est.
Time per case
1m 17s
1m 3s (better)
Quantization
BF16
BF16
Harness
openrouter
llama.cpp

The race

4 lead changes

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

FlintSpark X2.6 4B
0255075100501001502115

Every test case

153 test cases

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

26 won by Flint14 won by Spark X2.6 4B113 tied