Noometry

Model comparison

Qwen3.5 122B-A10B vs Step 3.7 Flash

Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 37.3 on the Noometry Index. Step 3.7 Flash costs 2.6× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.

Last verified . 3 shared benchmarks.

Qwen3.5 122B-A10B Alibaba (Qwen)

42.1

Rank #119 Confirmed

Step 3.7 Flash StepFun

37.3

Rank #207 Reported

Summary

  • They share 3 benchmarks with published results for both. Qwen3.5 122B-A10B scores higher in 1 category and Step 3.7 Flash in 2 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5 122B-A10B leads 27.2 to 21.6.
  • The biggest single-benchmark swing is NYT Connections (extended): 51.7% for Qwen3.5 122B-A10B and 39.7% for Step 3.7 Flash.
  • Step 3.7 Flash is cheaper at $0.18 / $1.11 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
  • Qwen3.5 122B-A10B accepts more context: 262K tokens versus 256K.

Side by side

Qwen3.5 122B-A10BStep 3.7 Flash
ProviderAlibaba (Qwen)StepFun
Noometry Index42.137.3
Released2026-02-232026-05-29
WeightsOpenOpen
Context window262K256K
Max output66K256K
Input $ / M tokens$0.40$0.18
Output $ / M tokens$3.20$1.11
Results tracked275

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Category by category

Coding Too close to call

Qwen3.5 122B-A10B: 39.1 (#162), Step 3.7 Flash: 40.0 (#150)

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
SciCode35.6%40%
LMArena WebDev1360—
LMArena Coding1436—
ALE-Bench—694.12

Reasoning Qwen3.5 122B-A10B leads

Qwen3.5 122B-A10B: 27.2 (#123), Step 3.7 Flash: 21.6 (#219)

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
NYT Connections (extended)51.7%39.7%
CritPt0.9%2.3%
Thematic Generalization51.2%—
LMArena Hard Prompts1421—
Mystery Game Puzzles17%—
DTBench84.3%—
LMCA32.2%—

Math Step 3.7 Flash leads

Qwen3.5 122B-A10B: 39.1 (#112), Step 3.7 Flash: 42.9 (#82)

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
MathArena Final-Answer Competitions—68.5%
LMArena Math1432—

Knowledge Not comparable

Qwen3.5 122B-A10B: 38.8 (#142), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
Vectara Hallucination Rate11.2%—
LMArena Expert1432—

Multimodal Not comparable

Qwen3.5 122B-A10B: 39.6 (#57), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
LMArena Vision1245—

Multilingual Not comparable

Qwen3.5 122B-A10B: 51.6 (#107), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
LMArena Non-English1400—
LMArena Chinese1462—
LMArena French1442—
LMArena German1426—
LMArena Japanese1367—
LMArena Korean1352—
LMArena Russian1400—
LMArena Spanish1424—

Instruction Following Not comparable

Qwen3.5 122B-A10B: 73.8 (#115), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
LMArena Instruction Following1399—

Long Context Not comparable

Qwen3.5 122B-A10B: 43.0 (#109), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
LMArena Longer Query1410—

Writing & Preference Not comparable

Qwen3.5 122B-A10B: 60.0 (#105), Step 3.7 Flash: —

BenchmarkQwen3.5 122B-A10BStep 3.7 Flash
LMArena Text1417—
LMArena Creative Writing1368—
LMArena Multi-Turn1416—

Frequently asked questions

Is Qwen3.5 122B-A10B better than Step 3.7 Flash?

Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 37.3 on the Noometry Index. Step 3.7 Flash costs 2.6× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.

Which is cheaper, Qwen3.5 122B-A10B 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; Qwen3.5 122B-A10B lists at $0.40 and $3.20.

Is Qwen3.5 122B-A10B or Step 3.7 Flash better for coding?

They score almost the same on coding (39.1 vs 40.0); test both on your own repository before choosing.

Which has the bigger context window?

Qwen3.5 122B-A10B does, with 262K tokens against 256K.

How many benchmarks do Qwen3.5 122B-A10B and Step 3.7 Flash share?

3 benchmarks have published results for both models. Qwen3.5 122B-A10B has 27 scored results on Noometry and Step 3.7 Flash has 5.

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