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Grok 4.5 vs Qwen3.7 Max

Updated October 21, 2026. 54 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Grok 4.5xAI
Coding
75.5
Overall
38.8
Output $/M
$6.00
43
Qwen3.7 MaxQwen
Coding
45.1
Overall
29.5
Output $/M
$4.425
11
vs boards won of 54 shared

Decision reading

Pick Grok 4.5 for coding: it scores 75.5 on the Vibe Coding Index against 45.1 for Qwen3.7 Max.

Pick Qwen3.7 Max when output tokens cost 1.4x less, or when the context window is larger, 1M against 500K tokens.

Shared results
54
Grok 4.5 only
66
Qwen3.7 Max only
5
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Grok 4.5 75.5 from 2 benchmarks, Qwen3.7 Max 45.1 from 1 benchmark.
Widest category
Coding, 9.8 points apart on average over 11 shared benchmarks.
Widest single gap
Code migration (Vals AI): Grok 4.5 36.6% against Qwen3.7 Max 13.1%, 23.5 points apart on a 0 to 100 scale.
Output price
Grok 4.5 $6.00 against Qwen3.7 Max $4.425 per million output tokens, 1.4x apart.
Context window
Grok 4.5 takes 500K tokens, Qwen3.7 Max 1M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGrok 4.5BarsQwen3.7 MaxTies
Coding110
Intelligence20
Agentic work121
Reasoning51
Math22
Knowledge33
Web design44
General40
All shared boards4311
CodingLike-for-likeFour of these boards feed the Vibe Coding Index110
Coding benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
LiveBench coding94.3%Not measuredOnly Grok 4.5 measured
LMArena WebDev15531515Grok 4.5
AA Coding Index72.466.0Grok 4.5
LiveCodeBench (Vals AI)87.3%87.1%Grok 4.5
SWE-bench Verified (Vals AI)86.6%68.8%Grok 4.5
Terminal-Bench 4 (Vals AI)8.6%Not measuredOnly Grok 4.5 measured
Vibe Code Bench (Vals AI)69.0%47.7%Grok 4.5
Code migration (Vals AI)36.6%13.1%Grok 4.5
ProgramBench (Vals AI)0.0%Not measuredOnly Grok 4.5 measured
IOI (Vals AI)40.6%Not measuredOnly Grok 4.5 measured
Terminal-Bench 2.1 (Vals AI)67.8%61.0%Grok 4.5
SkillsBench (Vals AI)66.0%Not measuredOnly Grok 4.5 measured
CyberBench (Vals AI)71.0%Not measuredOnly Grok 4.5 measured
SciCode55.0%49.5%Grok 4.5
Terminal-Bench Hard (Artificial Analysis run)Not measured50.8%Only Qwen3.7 Max measured
FrontierCode42.4%Not measuredOnly Grok 4.5 measured
WeirdML46.4%Not measuredOnly Grok 4.5 measured
ALE-Bench1309.31189.4Grok 4.5
LMArena Text: coding1474Not measuredOnly Grok 4.5 measured
LMArena Text: software and IT1471Not measuredOnly Grok 4.5 measured
LMArena WebDev: React15561514Grok 4.5
LMArena WebDev: HTML15671512Grok 4.5
LMArena WebDev: from an image1562Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
AA Intelligence Index38.829.5Grok 4.5
Epoch Capabilities Index154.1154.0Grok 4.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index121
Agentic work benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
AA Agentic Index41.222.5Grok 4.5
Design Arena: agents building web apps12171208Grok 4.5
Design Arena: agents building full-stack apps12491191Grok 4.5
Design Arena: agents building mobile apps12211153Grok 4.5
Design Arena: agents building Android apps12421165Grok 4.5
Design Arena: agents building Godot games12291187Grok 4.5
Design Arena: agents building games12351161Grok 4.5
Design Arena: HTML slides12041158Grok 4.5
Design Arena: PowerPoint slides12321196Grok 4.5
LiveBench research85.9%Not measuredOnly Grok 4.5 measured
LiveBench browser44.0%Not measuredOnly Grok 4.5 measured
LiveBench long agentic27.9%Not measuredOnly Grok 4.5 measured
SREBench (Vals AI)0.8%Not measuredOnly Grok 4.5 measured
Finance Agent (Vals AI)48.4%47.8%Grok 4.5
Tax Agent Bench (Vals AI)24.9%15.8%Grok 4.5
Legal Research Bench (Vals AI)38.0%25.5%Grok 4.5
Excel Modeling Benchmark (Vals AI)52.9%57.0%Qwen3.7 Max
Time Horizon Index (Vals AI)6.3%Not measuredOnly Grok 4.5 measured
τ²-Bench TelecomNot measured94.7%Only Qwen3.7 Max measured
APEX-Agents56.2%Not measuredOnly Grok 4.5 measured
PostTrainBench23.4%Not measuredOnly Grok 4.5 measured
Vending-Bench 2$3,887Not measuredOnly Grok 4.5 measured
LMArena Search1216Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
Reasoning benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
GPQA Diamond92.9%90.2%Grok 4.5
LiveBench reasoning87.2%Not measuredOnly Grok 4.5 measured
MMMU Pro (Vals AI)61.8%Not measuredOnly Grok 4.5 measured
GPQA Diamond (Artificial Analysis run)93.1%92.3%Grok 4.5
Humanity's Last Exam (Artificial Analysis run)42.7%40.5%Grok 4.5
GPQA Diamond (Epoch AI run)93.4%90.9%Grok 4.5
ARC-AGI87.2%Not measuredOnly Grok 4.5 measured
ARC-AGI-252.6%Not measuredOnly Grok 4.5 measured
SimpleBench70.0%70.4%Qwen3.7 Max
Chess puzzles35.0%26.0%Grok 4.5
Mystery game puzzlesNot measured32.0%Only Qwen3.7 Max measured
EBR-benchNot measured9.5%Only Qwen3.7 Max measured
LMArena Text: hard prompts1462Not measuredOnly Grok 4.5 measured
LMArena Text: expert1465Not measuredOnly Grok 4.5 measured
LMArena Text: hard prompts in English1464Not measuredOnly Grok 4.5 measured
LMArena Vision: diagrams1304Not measuredOnly Grok 4.5 measured
LMArena Vision: homework1295Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
OTIS Mock AIME97.8%95.6%Grok 4.5
FrontierMath, tiers 1 to 357.2%64.6%Qwen3.7 Max
FrontierMath, tier 424.4%34.1%Qwen3.7 Max
ProofBench31.0%26.0%Grok 4.5
LMArena Text: math1460Not measuredOnly Grok 4.5 measured
LMArena Text: mathematical work1482Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
Knowledge benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
MMLU Pro89.2%89.3%Qwen3.7 Max
LegalBench (Vals AI)86.0%84.9%Grok 4.5
CorpFin (Vals AI)67.4%63.7%Grok 4.5
TaxEval (Vals AI)71.7%75.3%Qwen3.7 Max
MortgageTax (Vals AI)61.8%Not measuredOnly Grok 4.5 measured
MedCode (Vals AI)43.3%38.8%Grok 4.5
SimpleQA Verified48.3%55.8%Qwen3.7 Max
LMArena Text: science1464Not measuredOnly Grok 4.5 measured
LMArena Text: medicine and healthcare1440Not measuredOnly Grok 4.5 measured
LMArena Text: legal and government1463Not measuredOnly Grok 4.5 measured
LMArena Text: business and finance1441Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index44
Web design benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
Design Arena: websites12811274Grok 4.5
Design Arena: UI components12791269Grok 4.5
Design Arena: game dev12631265Qwen3.7 Max
Design Arena: data viz12671275Qwen3.7 Max
Design Arena: 3D12571266Qwen3.7 Max
Design Arena: all code categories12761275Grok 4.5
Design Arena: SVG12151216Qwen3.7 Max
Design Arena: ASCII art12571211Grok 4.5
LiveBench design78.1%Not measuredOnly Grok 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
General benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
LiveBench data analysis73.0%Not measuredOnly Grok 4.5 measured
SAGE (Vals AI)35.0%Not measuredOnly Grok 4.5 measured
MedScribe (Vals AI)86.9%79.4%Grok 4.5
Vals Multimodal Index63.4%Not measuredOnly Grok 4.5 measured
IFBenchNot measured80.5%Only Qwen3.7 Max measured
Long context reasoning (AA-LCR)79.3%79.0%Grok 4.5
DTBench96.5%92.3%Grok 4.5
LMCA45.2%44.0%Grok 4.5
Surface Evolver Bench74.4%Not measuredOnly Grok 4.5 measured
Furniture assembly22.5%Not measuredOnly Grok 4.5 measured
LMArena Text1448Not measuredOnly Grok 4.5 measured
LMArena Text: instruction following1445Not measuredOnly Grok 4.5 measured
LMArena Text: creative writing1442Not measuredOnly Grok 4.5 measured
LMArena Vision1287Not measuredOnly Grok 4.5 measured
LMArena Text: English1453Not measuredOnly Grok 4.5 measured
LMArena Text: non-English1440Not measuredOnly Grok 4.5 measured
LMArena Text: Chinese1495Not measuredOnly Grok 4.5 measured
LMArena Text: German1448Not measuredOnly Grok 4.5 measured
LMArena Text: Japanese1430Not measuredOnly Grok 4.5 measured
LMArena Text: Korean1406Not measuredOnly Grok 4.5 measured
LMArena Text: French1457Not measuredOnly Grok 4.5 measured
LMArena Text: Spanish1451Not measuredOnly Grok 4.5 measured
LMArena Text: Russian1449Not measuredOnly Grok 4.5 measured
LMArena Text: Polish1432Not measuredOnly Grok 4.5 measured
LMArena Text: multi-turn1456Not measuredOnly Grok 4.5 measured
LMArena Text: longer queries1462Not measuredOnly Grok 4.5 measured
LMArena Text: writing and language1445Not measuredOnly Grok 4.5 measured
LMArena Text: entertainment and media1434Not measuredOnly Grok 4.5 measured
LMArena Vision: English1285Not measuredOnly Grok 4.5 measured
LMArena Vision: Chinese1345Not measuredOnly Grok 4.5 measured
LMArena Vision: reading text1293Not measuredOnly Grok 4.5 measured
LMArena Vision: humor1276Not measuredOnly Grok 4.5 measured
LMArena Vision: creative writing1293Not measuredOnly Grok 4.5 measured
LMArena Document1452Not measuredOnly Grok 4.5 measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Grok 4.5 and Qwen3.7 Max
BenchmarkGrok 4.5Qwen3.7 MaxLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Grok 4.5$0.0050Fits in one request
Qwen3.7 Max$0.0037Fits in one request

Qwen3.7 Max costs less

Repository review

50K input + 3K output tokens

Grok 4.5$0.118Fits in one request
Qwen3.7 Max$0.087Fits in one request

Qwen3.7 Max costs less

Agent loop

200K input + 10K output tokens

Grok 4.5$0.460Fits in one request
Qwen3.7 Max$0.339Fits in one request

Qwen3.7 Max costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Grok 4.5 and Qwen3.7 Max
SpecificationSpaceXAI Grok 4.5Qwen3.7 Max
MakerxAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedJuly 8, 2026May 21, 2026
Context window500K1M
Input $/Mtok$2.00$1.475
Output $/Mtok$6.00$4.425
Coding index75.545.1
Independent measurements behind it21
Cost per solved task$0.62$4.69
SourceOpenRouter listingOpenRouter listing

Questions

Is Grok 4.5 better than Qwen3.7 Max for coding?

Pick Grok 4.5 for coding: it scores 75.5 on the Vibe Coding Index against 45.1 for Qwen3.7 Max. Pick Qwen3.7 Max when output tokens cost 1.4x less, or when the context window is larger, 1M against 500K tokens.

Which is cheaper, Grok 4.5 or Qwen3.7 Max?

Grok 4.5 costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Per solved SWE-bench Verified task, Grok 4.5 costs $0.62 and Qwen3.7 Max $4.69.

Which has the bigger context window, Grok 4.5 or Qwen3.7 Max?

Qwen3.7 Max, with 1M tokens against 500K.

How many benchmarks is the Grok 4.5 vs Qwen3.7 Max comparison based on?

54 benchmarks have a result for both models as of October 21, 2026. Grok 4.5's coding index rests on 2 independent benchmarks and Qwen3.7 Max's on 1. Where only one model has a result, the page says so instead of naming a winner.

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