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Model comparison

Qwen3.5-122B-A10B vs Qwen3.7 Max

Data verified

Head-to-head evidence from 22 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

60.56/100
Margin
12.3pts
winning →
72.84/100
2 category wins4 category wins

Public leaderboard positions: Qwen3.5-122B-A10B #47 (Supported); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Qwen3.5-122B-A10B and Qwen3.7 Max share 22 comparable benchmark results. 6 of 8 categories are comparable. 9 results are unique to Qwen3.5-122B-A10B; 36 to Qwen3.7 Max.

Updated July 23, 2026
Shared results
22
Qwen3.5-122B-A10B only
9
Qwen3.7 Max only
36
Comparable categories
6 / 8

Pick Qwen3.7 Max if you want the stronger benchmark profile. Qwen3.5-122B-A10B only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 22 shared benchmark results across 6 evidence categories; 6 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.7 Max is clearly ahead on the BenchAlign aggregate, 72.84 to 60.56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.7 Max's sharpest advantage is in reasoning, where it averages 90.4 against 60.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 49.4% to 69.7%. Qwen3.5-122B-A10B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

Qwen3.7 Max gives you the larger context window at 1M, compared with 262K for Qwen3.5-122B-A10B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Qwen3.5-122B-A10B and Qwen3.7 Max
CategoryQwen3.5-122B-A10BΔQwen3.7 Max
ReasoningQwen3.5-122B-A10B60.2Margin→ 30.2Qwen3.7 Max90.4
KnowledgeQwen3.5-122B-A10B83.6Margin← 19.4Qwen3.7 Max64.2
AgenticQwen3.5-122B-A10B56.4Margin→ 13.3Qwen3.7 Max69.7
Inst. FollowingQwen3.5-122B-A10B93.4Margin← 9.0Qwen3.7 Max84.4
CodingQwen3.5-122B-A10B72.0Margin→ 5.9Qwen3.7 Max77.9
MultilingualQwen3.5-122B-A10B82.2Margin→ 4.8Qwen3.7 Max87.0
MathQwen3.5-122B-A10BNot measuredMarginNo overlapQwen3.7 Max97.1
MultimodalQwen3.5-122B-A10B77.2MarginNo overlapQwen3.7 MaxNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Qwen3.5-122B-A10BB · Qwen3.7 Max

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 49.4%B 69.7%
    Winner: Qwen3.7 MaxΔ 20.3
    Terminal-Bench 2.0: Qwen3.5-122B-A10B scored 49.4%; Qwen3.7 Max scored 69.7%. Qwen3.7 Max wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 72%B 80.4%
    Winner: Qwen3.7 MaxΔ 8.4
    SWE-bench Verified: Qwen3.5-122B-A10B scored 72%; Qwen3.7 Max scored 80.4%. Qwen3.7 Max wins this benchmark.

  3. SuperGPQA

    Knowledge
    Source ↗
    A 67.1%B 73.6%
    Winner: Qwen3.7 MaxΔ 6.5
    SuperGPQA: Qwen3.5-122B-A10B scored 67.1%; Qwen3.7 Max scored 73.6%. Qwen3.7 Max wins this benchmark.

  4. GPQA

    Knowledge
    Source ↗
    A 86.6%B 92.4%
    Winner: Qwen3.7 MaxΔ 5.8
    GPQA: Qwen3.5-122B-A10B scored 86.6%; Qwen3.7 Max scored 92.4%. Qwen3.7 Max wins this benchmark.

  5. MMLU-ProX

    Multilingual
    Source ↗
    A 82.2%B 87%
    Winner: Qwen3.7 MaxΔ 4.8
    MMLU-ProX: Qwen3.5-122B-A10B scored 82.2%; Qwen3.7 Max scored 87%. Qwen3.7 Max wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricQwen3.5-122B-A10BQwen3.7 MaxComparison
Input / output priceUSD per 1M tokensQwen3.5-122B-A10B$0 input / $0 outputQwen3.7 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondQwen3.5-122B-A10BNot availableQwen3.7 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenQwen3.5-122B-A10BNot availableQwen3.7 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensQwen3.5-122B-A10B262KQwen3.7 Max1MQwen3.7 Max lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.7 Max wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
Terminal-Bench 2.0Source 49.4%69.7%Qwen3.7 Max leads
BrowseCompSource 63.8%—Not comparable
OSWorld-VerifiedSource 58%—Not comparable
τ²-bench resultsSource 93.6%94.7%Qwen3.7 Max leads
AA Agentic IndexSource 20.7%30.6%Qwen3.7 Max leads
GDPval-AASource 23.9%38.7%Qwen3.7 Max leads
GDPval-AASource 9781273Qwen3.7 Max leads
QwenClawBenchSource —64.3%Not comparable
QwenWebBenchSource —1568Not comparable
Claw-EvalSource —65.2%Not comparable
BFCL v4Source —75.0%Not comparable
MCP AtlasSource —76.4%Not comparable
VITA-BenchSource —47.9%Not comparable
HLE w/ toolsSource —53.5%Not comparable
Gert LabsSource —64.27%Not comparable
ResearchClawBenchSource —18.7%Not comparable
AA BriefcaseSource —908Not comparable
AA AutomationBenchSource —25.6%Not comparable
AA EnterpriseOps-GymSource —45.0%Not comparable
AA ITBenchSource —42.5%Not comparable
terminalBenchHardSource —50.8%Not comparable
aaTerminalBench21Source —74.5%Not comparable
AA Harvey LABSource —83.4%Not comparable
CodingQwen3.7 Max wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
SWE-bench VerifiedSource 72%80.4%Qwen3.7 Max leads
AA Coding IndexSource 45.7%66.0%Qwen3.7 Max leads
AA-SciCodeSource 42.0%48.8%Qwen3.7 Max leads
SWE-bench ProSource —60.6%Not comparable
SWE MultilingualSource —78.3%Not comparable
NL2RepoSource —47.2%Not comparable
SciCodeSource —53.5%Not comparable
LiveCodeBenchSource —91.6%Not comparable
Terminal-Bench 2.0Source —69.7%Not comparable
ReasoningQwen3.7 Max wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
LongBench v2Source 60.2%—Not comparable
AA-LCRSource 66.7%69.0%Qwen3.7 Max leads
CritPtSource 0.6%13.4%Qwen3.7 Max leads
MRCRv2Source —90.4%Not comparable
KnowledgeQwen3.5-122B-A10B wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
MMLU-ProSource 86.7%89.6%Qwen3.7 Max leads
SuperGPQASource 67.1%73.6%Qwen3.7 Max leads
GPQASource 86.6%92.4%Qwen3.7 Max leads
Artificial Analysis Intelligence IndexSource 32.3%46.0%Qwen3.7 Max leads
AA-GPQA DiamondSource 85.7%92.3%Qwen3.7 Max leads
AA-HLESource 23.4%38.1%Qwen3.7 Max leads
AA-Omniscience IndexSource -39.6%14.1%Qwen3.7 Max leads
AA-Omniscience AccuracySource 24.7%30.1%Qwen3.7 Max leads
AA-Omniscience Hallucination RateSource 85.5%22.9%Qwen3.7 Max leads
GPQA-DSource —92.4%Not comparable
HLESource —41.4%Not comparable
MMLU-ReduxSource —95%Not comparable
MMMLUSource —90.3%Not comparable
Math
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
HMMT Feb 2026Source —97.1%Not comparable
IMOAnswerBenchSource —90.0%Not comparable
ApexSource —44.5%Not comparable
MultilingualQwen3.7 Max wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
MMLU-ProXSource 82.2%87%Qwen3.7 Max leads
NOVA-63Source —59.0%Not comparable
INCLUDESource —86.2%Not comparable
MAXIFESource —89.2%Not comparable
PolyMathSource —86.5%Not comparable
Multimodal
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
MMMUSource 83.9%—Not comparable
MMVUSource 74.7%—Not comparable
MathVisionSource 86.2%—Not comparable
CharXivSource 77.2%—Not comparable
V*Source 93.2%—Not comparable
AA-MMMU-ProSource 75.0%—Not comparable
Design Arena WebsiteSource —1293Not comparable
Inst. FollowingQwen3.5-122B-A10B wins
BenchmarkQwen3.5-122B-A10BQwen3.7 MaxResult
IFEvalSource 93.4%94.3%Qwen3.7 Max leads
AA-IFBenchSource 75.7%80.5%Qwen3.7 Max leads
IFBenchSource —79.1%Not comparable
Frequently Asked Questions (7)

Which is better, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.7 Max is ahead on BenchLM's BenchAlign leaderboard, 72.84 to 60.56. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 49.4% and 69.7%.

Which is better for knowledge tasks, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 83.6 versus 64.2. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 versus 72. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for reasoning, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.7 Max has the edge for reasoning in this comparison, averaging 90.4 versus 60.2. Inside this category, CritPt is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.7 Max has the edge for agentic tasks in this comparison, averaging 69.7 versus 56.4. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for instruction following, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.5-122B-A10B has the edge for instruction following in this comparison, averaging 93.4 versus 84.4. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.

Which is better for multilingual tasks, Qwen3.5-122B-A10B or Qwen3.7 Max?

Qwen3.7 Max has the edge for multilingual tasks in this comparison, averaging 87 versus 82.2. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.

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