Model comparison

Qwen2.5-Coder-32B vs Step 3.7 Flash

Step 3.7 Flash is the stronger model overall, scoring 37.3 to 33.4 on the Noometry Index.

Last verified October 11, 2026. 0 shared benchmarks.

Qwen2.5-Coder-32B

Alibaba (Qwen)

33.4

Rank #245 Confirmed

Step 3.7 Flash

StepFun

37.3

Rank #207 Reported

Summary

The widest gap is in coding, where Step 3.7 Flash leads 40.0 to 22.6.
Step 3.7 Flash is cheaper at $0.18 / $1.11 per million input/output tokens, against $0.66 / $1 for Qwen2.5-Coder-32B.
Step 3.7 Flash accepts more context: 256K tokens versus 33K.

Side by side

Qwen2.5-Coder-32B and Step 3.7 Flash specifications
	Qwen2.5-Coder-32B	Step 3.7 Flash
Provider	Alibaba (Qwen)	StepFun
Noometry Index	33.4	37.3
Released	2024-09-18	2026-05-29
Weights	Open	Open
Context window	33K	256K
Max output	29K	256K
Input $ / M tokens	$0.66	$0.18
Output $ / M tokens	$1	$1.11
Results tracked	31	5

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Category by category

Coding Step 3.7 Flash leads

Qwen2.5-Coder-32B: 22.6 (#333), Step 3.7 Flash: 40.0 (#150)

Coding benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
SWE-bench Verified (bash only)	9%	—
Aider Polyglot	16.4%	—
SciCode	—	40%
BigCodeBench Instruct	49%	—
LiveBench Coding	56.9%	—
LMArena Coding	1276	—
BigCodeBench Complete	58%	—
ALE-Bench	—	694.12
HumanEval+	87.2%	—
MBPP+	77%	—

Reasoning Too close to call

Qwen2.5-Coder-32B: 21.2 (#225), Step 3.7 Flash: 21.6 (#219)

Reasoning benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
NYT Connections (extended)	—	39.7%
CritPt	—	2.3%
LiveBench Reasoning	42.1%	—
LMArena Hard Prompts	1251	—
LiveBench Data Analysis	49.9%	—
Epoch Capabilities Index	119.49	—
HellaSwag	83%	—
LiveBench	46.2%	—
WinoGrande	80.8%	—

Math Step 3.7 Flash leads

Qwen2.5-Coder-32B: 33.3 (#204), Step 3.7 Flash: 42.9 (#82)

Math benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
MathArena Final-Answer Competitions	—	68.5%
LiveBench Math	46.6%	—
LMArena Math	1251	—
GSM8K	93%	—

Knowledge Not comparable

Qwen2.5-Coder-32B: 33.4 (#203), Step 3.7 Flash: —

Knowledge benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
LMArena Expert	1221	—
ARC (AI2) Challenge	70.5%	—
MMLU	79.1%	—

Multilingual Not comparable

Qwen2.5-Coder-32B: 37.8 (#235), Step 3.7 Flash: —

Multilingual benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
LMArena Non-English	1205	—
LMArena Chinese	1222	—
LMArena Russian	1228	—

Instruction Following Not comparable

Qwen2.5-Coder-32B: 61.4 (#245), Step 3.7 Flash: —

Instruction Following benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
LiveBench Instruction Following	58.7%	—
LMArena Instruction Following	1223	—

Long Context Not comparable

Qwen2.5-Coder-32B: 38.0 (#208), Step 3.7 Flash: —

Long Context benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
LMArena Longer Query	1251	—

Writing & Preference Not comparable

Qwen2.5-Coder-32B: 41.6 (#240), Step 3.7 Flash: —

Writing & Preference benchmarks
Benchmark	Qwen2.5-Coder-32B	Step 3.7 Flash
LMArena Text	1230	—
LMArena Creative Writing	1174	—
LMArena Multi-Turn	1222	—
LiveBench Language	23.3%	—

Frequently asked questions

Is Qwen2.5-Coder-32B better than Step 3.7 Flash?

Step 3.7 Flash is the stronger model overall, scoring 37.3 to 33.4 on the Noometry Index.

Which is cheaper, Qwen2.5-Coder-32B or Step 3.7 Flash?

Step 3.7 Flash is cheaper. It lists at $0.18 per million input tokens and $1.11 per million output tokens; Qwen2.5-Coder-32B lists at $0.66 and $1.

Is Qwen2.5-Coder-32B or Step 3.7 Flash better for coding?

Step 3.7 Flash scores higher on coding benchmarks: 40.0 versus 22.6 in the Noometry coding category.

Which has the bigger context window?

Step 3.7 Flash does, with 256K tokens against 33K.

How many benchmarks do Qwen2.5-Coder-32B and Step 3.7 Flash share?

0 benchmarks have published results for both models. Qwen2.5-Coder-32B has 31 scored results on Noometry and Step 3.7 Flash has 5.