Model comparison

DeepSeek V4 Pro vs Qwen2.5-Coder (1.5B)

DeepSeek V4 Pro has enough public results to be ranked (#28); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.

Last verified . 1 shared benchmarks.

Summary

  • They share 1 benchmark with published results for both.

Side by side

DeepSeek V4 Pro and Qwen2.5-Coder (1.5B) specifications
DeepSeek V4 ProQwen2.5-Coder (1.5B)
ProviderDeepSeekAlibaba (Qwen)
Noometry Index54.2—
Released2026-04-242024-09-18
WeightsOpenOpen
Context window1M—
Max output393K—
Input $ / M tokens$0.43—
Output $ / M tokens$0.87—
Results tracked486

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Category by category

Coding Not comparable

DeepSeek V4 Pro: 52.2 (#31), Qwen2.5-Coder (1.5B): —

Coding benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
SWE-bench Verified77.6%—
FrontierCode28.6%—
LMArena WebDev1582—
SciCode51%—
WeirdML66.2%—
LMArena Coding1470—
ALE-Bench1,403—

Agentic & Tool Use Not comparable

DeepSeek V4 Pro: 32.7 (#54), Qwen2.5-Coder (1.5B): —

Agentic & Tool Use benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
APEX-Agents47.3%—
Vending-Bench 23,285—

Reasoning Not comparable

DeepSeek V4 Pro: 56.4 (#22), Qwen2.5-Coder (1.5B): —

Reasoning benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
Epoch Capabilities Index155.39112.93
ARC-AGI-261.3%—
Kagi LLM Benchmark53.5%—
NYT Connections (extended)91.3%—
ARC-AGI-190.5%—
CritPt18%—
Chess Puzzles47%—
LMArena Hard Prompts1461—
Mystery Game Puzzles43%—
DTBench93.9%—
LMCA45.5%—
Surface Evolver Bench40%—
ForecastBench56.1—
HellaSwag—76.8%
WinoGrande—72.9%

Math Not comparable

DeepSeek V4 Pro: 64.6 (#24), Qwen2.5-Coder (1.5B): —

Math benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
FrontierMath (Tiers 1-3)64.6%—
FrontierMath Tier 426.8%—
MathArena Final-Answer Competitions76.6%—
OTIS Mock AIME 2024-202598.6%—
ProofBench50%—
LMArena Math1455—
GSM8K—86.7%

Knowledge Not comparable

DeepSeek V4 Pro: 59.5 (#28), Qwen2.5-Coder (1.5B): —

Knowledge benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
GPQA Diamond91.7%—
SimpleQA Verified52.9%—
Vectara Hallucination Rate8.6%—
LMArena Expert1463—
ARC (AI2) Challenge—60.9%
MMLU—68%

Multilingual Not comparable

DeepSeek V4 Pro: 54.5 (#44), Qwen2.5-Coder (1.5B): —

Multilingual benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
LMArena Non-English1438—
LMArena Chinese1486—
LMArena French1473—
LMArena German1458—
LMArena Japanese1448—
LMArena Korean1452—
LMArena Russian1452—
LMArena Spanish1457—

Instruction Following Not comparable

DeepSeek V4 Pro: 76.3 (#44), Qwen2.5-Coder (1.5B): —

Instruction Following benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
LMArena Instruction Following1448—

Long Context Not comparable

DeepSeek V4 Pro: 45.0 (#49), Qwen2.5-Coder (1.5B): —

Long Context benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
CL-bench Life13.5%—
LMArena Longer Query1459—

Writing & Preference Not comparable

DeepSeek V4 Pro: 65.6 (#45), Qwen2.5-Coder (1.5B): —

Writing & Preference benchmarks
BenchmarkDeepSeek V4 ProQwen2.5-Coder (1.5B)
LMArena Text1451—
LMArena Creative Writing1446—
EQ-Bench Creative Writing1553—
EQ-Bench 41166—
LMArena Multi-Turn1467—

Frequently asked questions

Is DeepSeek V4 Pro better than Qwen2.5-Coder (1.5B)?

DeepSeek V4 Pro has enough public results to be ranked (#28); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.

How many benchmarks do DeepSeek V4 Pro and Qwen2.5-Coder (1.5B) share?

1 benchmark has published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Qwen2.5-Coder (1.5B) has 6.

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