DeepSeek V4.1 Flash vs GLM 5.3 Flash

Overall
64
vs
Overall
35

DeepSeek V4.1 Flash is clearly better. It wins 62 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. DeepSeek V4.1 Flash spends 2.2× as many thinking tokens per test case.

Thinking tokensAnswer tokens
TaskAB
Overall
643m 35s
6K, 91% thinking2.8K, 89% thinking
3555.5s
Agents
464m 42s
6.1K, 82% thinking607, 81% thinking
1037.0s
Structured Extraction
862m 8s
4.4K, 94% thinking2.7K, 93% thinking
4847.2s
Coding
514m 55s
9.7K, 95% thinking5.3K, 83% thinking
541m 52s
Grounded Answers
762m 17s
3.9K, 90% thinking2.9K, 93% thinking
3756.8s
Instruction Following
894m 24s
7.5K, 94% thinking2K, 77% thinking
4340.8s
Business Logic
814m 1s
7K, 97% thinking5.8K, 98% thinking
331m 18s
Security & permissions
693m 3s
4.4K, 81% thinking963, 81% thinking
5525.2s
Diagnosis & investigation
172m 8s
3.2K, 67% thinking563, 63% thinking
027.0s

What you'd run

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

SpecAB
Speed
30 tok/s
60 tok/s (better)
Machine
Hosted
Hosted
Memory at 32K
—
—
Context
1M
1M
Cost per run
$0.39
$0.19 (better)
Cost per case
$0.0026
$0.0013 (better)
Time per case
3m 35s
55.5s (better)
Quantization
FP8
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.

DeepSeek V4.1 FlashGLM 5.3 Flash
025507510050100150Perfect run6435

Every test case

153 test cases

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

62 won by DeepSeek V4.1 Flash7 won by GLM 5.3 Flash84 tied