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Model comparison

GPT-5.3 Codex vs Qwen3.7 Max

Data verified

Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.69/100
Margin
6.2pts
winning →
72.84/100
1 category wins1 category wins

Public leaderboard positions: GPT-5.3 Codex #26 (Supported); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.3 Codex and Qwen3.7 Max share 16 comparable benchmark results. 2 of 8 categories are comparable. 5 results are unique to GPT-5.3 Codex; 42 to Qwen3.7 Max.

Updated July 23, 2026
Shared results
16
GPT-5.3 Codex only
5
Qwen3.7 Max only
42
Comparable categories
2 / 8

Pick Qwen3.7 Max if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if agentic is the priority.

Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 2 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 66.69. 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 coding, where it averages 77.9 against 67.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 69.7%. GPT-5.3 Codex does hit back in agentic, 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 400K for GPT-5.3 Codex.

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 GPT-5.3 Codex and Qwen3.7 Max
CategoryGPT-5.3 CodexΔQwen3.7 Max
CodingGPT-5.3 Codex67.2Margin→ 10.7Qwen3.7 Max77.9
AgenticGPT-5.3 Codex71.4Margin← 1.7Qwen3.7 Max69.7
ReasoningGPT-5.3 CodexNot measuredMarginNo overlapQwen3.7 Max90.4
KnowledgeGPT-5.3 CodexNot measuredMarginNo overlapQwen3.7 Max64.2
MathGPT-5.3 CodexNot measuredMarginNo overlapQwen3.7 Max97.1
MultilingualGPT-5.3 CodexNot measuredMarginNo overlapQwen3.7 Max87.0
Inst. FollowingGPT-5.3 CodexNot measuredMarginNo overlapQwen3.7 Max84.4

Decisive benchmark drivers

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

More
A · GPT-5.3 CodexB · Qwen3.7 Max

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 77.3%B 69.7%
    Winner: GPT-5.3 CodexΔ 7.6
    Terminal-Bench 2.0: GPT-5.3 Codex scored 77.3%; Qwen3.7 Max scored 69.7%. GPT-5.3 Codex wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 85%B 80.4%
    Winner: GPT-5.3 CodexΔ 4.6
    SWE-bench Verified: GPT-5.3 Codex scored 85%; Qwen3.7 Max scored 80.4%. GPT-5.3 Codex wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 56.8%B 60.6%
    Winner: Qwen3.7 MaxΔ 3.8
    SWE-bench Pro: GPT-5.3 Codex scored 56.8%; Qwen3.7 Max scored 60.6%. Qwen3.7 Max wins this benchmark.

Operational comparison

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

MetricGPT-5.3 CodexQwen3.7 MaxComparison
Input / output priceUSD per 1M tokensGPT-5.3 Codex$1.75 input / $14 outputQwen3.7 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondGPT-5.3 Codex79 tok/sQwen3.7 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.3 Codex88.26 sQwen3.7 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.3 Codex400KQwen3.7 Max1MQwen3.7 Max lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.3 Codex wins
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
Terminal-Bench 2.0Source 77.3%69.7%GPT-5.3 Codex leads
OSWorld-VerifiedSource 64.7%—Not comparable
τ²-bench resultsSource 86%94.7%Qwen3.7 Max leads
Gert LabsSource 57.47%64.27%Qwen3.7 Max leads
JobBenchSource 33.7%—Not comparable
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
AA Agentic IndexSource —30.6%Not comparable
GDPval-AASource —38.7%Not comparable
GDPval-AASource —1273Not 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
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
SWE-bench VerifiedSource 85%80.4%GPT-5.3 Codex leads
SWE-bench ProSource 56.8%60.6%Qwen3.7 Max leads
SWE-RebenchSource 58.2%—Not comparable
Vibe Code BenchSource 61.77%—Not comparable
AA-SciCodeSource 53.2%48.8%GPT-5.3 Codex leads
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
AA Coding IndexSource —66.0%Not comparable
Reasoning
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
AA-LCRSource 74.0%69.0%GPT-5.3 Codex leads
CritPtSource 16.9%13.4%GPT-5.3 Codex leads
MRCRv2Source —90.4%Not comparable
Knowledge
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
Artificial Analysis Intelligence IndexSource 44.3%46.0%Qwen3.7 Max leads
AA-GPQA DiamondSource 91.5%92.3%Qwen3.7 Max leads
AA-HLESource 39.9%38.1%GPT-5.3 Codex leads
AA-Omniscience IndexSource 9.9%14.1%Qwen3.7 Max leads
AA-Omniscience AccuracySource 51.8%30.1%GPT-5.3 Codex leads
AA-Omniscience Hallucination RateSource 86.9%22.9%Qwen3.7 Max leads
GPQASource —92.4%Not comparable
GPQA-DSource —92.4%Not comparable
HLESource —41.4%Not comparable
MMLU-ProSource —89.6%Not comparable
MMLU-ReduxSource —95%Not comparable
SuperGPQASource —73.6%Not comparable
MMMLUSource —90.3%Not comparable
Math
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
HMMT Feb 2026Source —97.1%Not comparable
IMOAnswerBenchSource —90.0%Not comparable
ApexSource —44.5%Not comparable
Multilingual
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
MMLU-ProXSource —87%Not comparable
NOVA-63Source —59.0%Not comparable
INCLUDESource —86.2%Not comparable
MAXIFESource —89.2%Not comparable
PolyMathSource —86.5%Not comparable
Multimodal
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
AA-MMMU-ProSource 78.5%—Not comparable
Design Arena WebsiteSource 11931293Qwen3.7 Max leads
Inst. Following
BenchmarkGPT-5.3 CodexQwen3.7 MaxResult
AA-IFBenchSource 75.4%80.5%Qwen3.7 Max leads
IFEvalSource —94.3%Not comparable
IFBenchSource —79.1%Not comparable
Frequently Asked Questions (3)

Which is better, GPT-5.3 Codex or Qwen3.7 Max?

Qwen3.7 Max is ahead on BenchLM's BenchAlign leaderboard, 72.84 to 66.69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 69.7%.

Which is better for coding, GPT-5.3 Codex or Qwen3.7 Max?

Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 versus 67.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GPT-5.3 Codex or Qwen3.7 Max?

GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 69.7. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.

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