BenchmarksToday
Qwen2.5-Coder-32B-Instruct — LiveBench Scores
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
View sourceQwen
Significantly improvements in code generation, code reasoning and code fixing. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc.
Running this yourself: likely needs a rented cloud gpu.
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55.6
Quality Score
1232
Arena ELO
33B
Parameters
33K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
19 of 22 public signals
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841.1K
Downloads
2.2K
Likes
Nov 2024
Released
5/5 signals
4/4 signals
4/5 signals
3/4 signals
3/4 signals
Parameters
33B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
Benchmarks
19
Open Source
1
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
View sourceSWE-Bench Verified resolved rate 47.0
View sourcelanguage: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
View sourcelanguage: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
View sourceQwen2.5-Coder-32B-Instruct is now available through local Ollama runtime. 32K context window listed. The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and code fixing.
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
SWE-Bench Verified resolved rate 47.0
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5
language: 0.3 | coding: 0.8 | instruction_following: 0.3 | Overall: 0.5