Muse Spark 1.3 Contributor vs Spark X2.6 4B

Overall
66
vs
Overall
15

Muse Spark 1.3 Contributor is clearly better. It wins 93 of the 94 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. Muse Spark 1.3 Contributor spends 1.2× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
661m 42s
8.7K, 91% thinking8.2K, 84% thinking
151m 3s
Agents
573m 16s
14.7K, 88% thinking11.5K, 97% thinking
141m 32s
Structured Extraction
9037.9s
4.2K, 91% thinking5.3K, 78% thinking
1039.5s
Coding
482m 1s
10.8K, 95% thinking9.1K, 48% thinking
41m 8s
Grounded Answers
811m 1s
6.1K, 91% thinking6.6K, 86% thinking
1050.2s
Instruction Following
841m 18s
8.7K, 91% thinking11.9K, 90% thinking
371m 29s
Business Logic
761m 7s
6K, 95% thinking4.9K, 86% thinking
1036.3s
Security & permissions
761m 59s
8.2K, 87% thinking7K, 94% thinking
3154.3s
Diagnosis & investigation
173m 34s
17.2K, 90% 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
107 tok/s
136 tok/s
Machine
Hosted
RTX 5090, 32 GB
Memory at 32K
—
9.4 GB
Context
1M (better)
605K
Cost per run
$0.41 (better)
$1.61 est.
Cost per case
$0.0027 (better)
$0.011 est.
Time per case
1m 42s
1m 3s (better)
Quantization
—
BF16
Harness
openrouter
llama.cpp

The race

No lead changes

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

Muse Spark 1.3 ContributorSpark X2.6 4B
0255075100501001506615

Every test case

153 test cases

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

93 won by Muse Spark 1.3 Contributor1 won by Spark X2.6 4B59 tied