GLM 5.3 Flash vs Muse Spark 1.3 Contributor

Overall
35
vs
Overall
66

Muse Spark 1.3 Contributor is clearly better. It wins 63 of the 69 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 3.2× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
3555.5s
2.8K, 89% thinking8.7K, 91% thinking
661m 42s
Agents
1037.0s
607, 81% thinking14.7K, 88% thinking
573m 16s
Structured Extraction
4847.2s
2.7K, 93% thinking4.2K, 91% thinking
9037.9s
Coding
541m 52s
5.3K, 83% thinking10.8K, 95% thinking
482m 1s
Grounded Answers
3756.8s
2.9K, 93% thinking6.1K, 91% thinking
811m 1s
Instruction Following
4340.8s
2K, 77% thinking8.7K, 91% thinking
841m 18s
Business Logic
331m 18s
5.8K, 98% thinking6K, 95% thinking
761m 7s
Security & permissions
5525.2s
963, 81% thinking8.2K, 87% thinking
761m 59s
Diagnosis & investigation
027.0s
563, 63% thinking17.2K, 90% thinking
173m 34s

What you'd run

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

SpecAB
Speed
60 tok/s
107 tok/s (better)
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
1M
1M
Cost per run
$0.19 (better)
$0.41
Cost per case
$0.0013 (better)
$0.0027
Time per case
55.5s (better)
1m 42s
Quantization
FP8
—
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.

GLM 5.3 FlashMuse Spark 1.3 Contributor
025507510050100150Perfect run3566

Every test case

153 test cases

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

6 won by GLM 5.3 Flash63 won by Muse Spark 1.3 Contributor84 tied