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Grok 4.7 vs Qwen3.8 Max (0902)

Updated October 21, 2026. 89 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Grok 4.7 Replace Qwen3.8 Max (0902)
Grok 4.7xAI
Coding
75.0
Overall
46.4
Output $/M
$6.00
26
Qwen3.8 Max (0902)Qwen
Coding
63.5
Overall
45.4
Output $/M
$6.00
62
vs boards won of 89 shared, 1 tied

Decision reading

Pick Grok 4.7 for coding: it scores 75.0 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902).

Pick Qwen3.8 Max (0902) when the context window is larger, 1M against 500K tokens, or when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.

Model AGrok 4.7xAI75.0/1002 independent benchmarksNo cost per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
Shared results
89
Grok 4.7 only
10
Qwen3.8 Max (0902) only
24
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 4.7 75.0 from 2 benchmarks, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
Widest category
Math, 18.2 points apart on average over 6 shared benchmarks.
Widest single gap
CyberBench (Vals AI): Grok 4.7 69.5% against Qwen3.8 Max (0902) 28.6%, 40.9 points apart on a 0 to 100 scale.
Output price
Both cost $6.00 per million output tokens.
Context window
Grok 4.7 takes 500K tokens, Qwen3.8 Max (0902) 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 4.7BarsQwen3.8 Max (0902)Ties
Coding98
Intelligence11
Agentic work63
Reasoning281 tie
Math06
Knowledge34
Web design16
General426
All shared boards26621 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index98
Coding benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
LiveBench coding84.5%60.3%Grok 4.7
LMArena WebDev16371674Qwen3.8 Max (0902)
AA Coding IndexNot measured76.2Only Qwen3.8 Max (0902) measured
LiveCodeBench (Vals AI)Not measured87.8%Only Qwen3.8 Max (0902) measured
SWE-bench Verified (Vals AI)Not measured85.6%Only Qwen3.8 Max (0902) measured
Terminal-Bench 4 (Vals AI)28.8%34.3%Qwen3.8 Max (0902)
Vibe Code Bench (Vals AI)86.2%64.7%Grok 4.7
Code migration (Vals AI)44.8%24.0%Grok 4.7
ProgramBench (Vals AI)0.5%0.0%Grok 4.7
IOI (Vals AI)57.7%68.9%Qwen3.8 Max (0902)
Terminal-Bench 2.1 (Vals AI)73.4%67.4%Grok 4.7
SWE-bench Multimodal (Vals AI)42.9%42.5%Grok 4.7
Vibe Code Bench 1-100 (Vals AI)Not measured12.8%Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)Not measured42.0%Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)69.5%28.6%Grok 4.7
SciCode57.8%53.2%Grok 4.7
FrontierCode47.6%Not measuredOnly Grok 4.7 measured
FrontierSWE29.5%17.8%Grok 4.7
LMArena Text: coding14321502Qwen3.8 Max (0902)
LMArena Text: software and IT14211498Qwen3.8 Max (0902)
LMArena WebDev: React16631692Qwen3.8 Max (0902)
LMArena WebDev: HTML16271649Qwen3.8 Max (0902)
LMArena WebDev: from an image15861637Qwen3.8 Max (0902)
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
AA Intelligence Index46.445.4Grok 4.7
Epoch Capabilities Index154.4157.4Qwen3.8 Max (0902)
Agentic workLike-for-likePublic boards, shown as published, kept out of the index63
Agentic work benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
AA Agentic IndexNot measured56.0Only Qwen3.8 Max (0902) measured
Design Arena: agents building web appsNot measured1301Only Qwen3.8 Max (0902) measured
Design Arena: agents building full-stack appsNot measured1305Only Qwen3.8 Max (0902) measured
Design Arena: agents building mobile appsNot measured1223Only Qwen3.8 Max (0902) measured
Design Arena: agents building Android appsNot measured1207Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot gamesNot measured1234Only Qwen3.8 Max (0902) measured
Design Arena: PowerPoint slidesNot measured1257Only Qwen3.8 Max (0902) measured
Design Arena: spreadsheetsNot measured868Only Qwen3.8 Max (0902) measured
LiveBench research86.4%69.9%Grok 4.7
LiveBench browser60.0%32.0%Grok 4.7
LiveBench long agentic50.1%42.3%Grok 4.7
SREBench (Vals AI)3.8%Not measuredOnly Grok 4.7 measured
Finance Agent (Vals AI)52.3%50.6%Grok 4.7
Tax Agent Bench (Vals AI)34.2%32.1%Grok 4.7
Legal Research Bench (Vals AI)47.1%47.6%Qwen3.8 Max (0902)
Harvey's Legal Agent Benchmark (Vals AI)18.3%Not measuredOnly Grok 4.7 measured
Excel Modeling Benchmark (Vals AI)67.0%60.1%Grok 4.7
BioMysteryBench (Vals AI)69.3%Not measuredOnly Grok 4.7 measured
Terminal-Bench-Science (Vals AI)10.0%12.9%Qwen3.8 Max (0902)
Vals Science Index34.8%Not measuredOnly Grok 4.7 measured
Robo-bench (Vals AI)0.2%Not measuredOnly Grok 4.7 measured
APEX-Agents54.6%63.3%Qwen3.8 Max (0902)
Vending-Bench 2$10,537Not measuredOnly Grok 4.7 measured
LMArena SearchNot measured1261Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 15 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index28
Reasoning benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
GPQA DiamondNot measured93.7%Only Qwen3.8 Max (0902) measured
LiveBench reasoning82.7%88.2%Qwen3.8 Max (0902)
MysteryMechanism (Vals AI)25.2%23.9%Grok 4.7
MMMU Pro (Vals AI)Not measured88.0%Only Qwen3.8 Max (0902) measured
GPQA Diamond (Artificial Analysis run)Not measured92.8%Only Qwen3.8 Max (0902) measured
Humanity's Last Exam (Artificial Analysis run)43.1%43.1%Tie
GPQA Diamond (Epoch AI run)92.7%92.7%Grok 4.7
ARC-AGI90.2%Not measuredOnly Grok 4.7 measured
ARC-AGI-261.4%Not measuredOnly Grok 4.7 measured
Chess puzzles41.0%46.0%Qwen3.8 Max (0902)
Mystery game puzzles29.0%38.0%Qwen3.8 Max (0902)
LMArena Text: hard prompts14151496Qwen3.8 Max (0902)
LMArena Text: expert14391507Qwen3.8 Max (0902)
LMArena Text: hard prompts in English14271503Qwen3.8 Max (0902)
LMArena Vision: diagrams12541323Qwen3.8 Max (0902)
LMArena Vision: homework13091336Qwen3.8 Max (0902)
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index06
Math benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
OTIS Mock AIME98.1%100.0%Qwen3.8 Max (0902)
FrontierMath, tiers 1 to 353.0%74.7%Qwen3.8 Max (0902)
FrontierMath, tier 417.1%46.3%Qwen3.8 Max (0902)
ProofBench26.0%58.0%Qwen3.8 Max (0902)
LMArena Text: math14141501Qwen3.8 Max (0902)
LMArena Text: mathematical work14351491Qwen3.8 Max (0902)
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index34
Knowledge benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
MMLU ProNot measured88.6%Only Qwen3.8 Max (0902) measured
LegalBench (Vals AI)84.4%83.6%Grok 4.7
CorpFin (Vals AI)Not measured65.8%Only Qwen3.8 Max (0902) measured
TaxEval (Vals AI)Not measured75.5%Only Qwen3.8 Max (0902) measured
MortgageTax (Vals AI)Not measured64.0%Only Qwen3.8 Max (0902) measured
MedCode (Vals AI)49.5%40.7%Grok 4.7
SimpleQA Verified56.0%47.3%Grok 4.7
LMArena Text: science14191512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare13951503Qwen3.8 Max (0902)
LMArena Text: legal and government14231492Qwen3.8 Max (0902)
LMArena Text: business and finance13891480Qwen3.8 Max (0902)
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
Design Arena: websites12551275Qwen3.8 Max (0902)
Design Arena: UI components12711340Qwen3.8 Max (0902)
Design Arena: game dev13141313Grok 4.7
Design Arena: data viz12271281Qwen3.8 Max (0902)
Design Arena: 3D12691337Qwen3.8 Max (0902)
Design Arena: all code categories12711293Qwen3.8 Max (0902)
Design Arena: ASCII artNot measured1201Only Qwen3.8 Max (0902) measured
LiveBench design78.0%78.6%Qwen3.8 Max (0902)
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index426
General benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
Vals Index58.6%Not measuredOnly Grok 4.7 measured
LiveBench data analysis76.9%78.4%Qwen3.8 Max (0902)
Public Benefits Bench (Vals AI)65.6%67.1%Qwen3.8 Max (0902)
SAGE (Vals AI)40.8%51.2%Qwen3.8 Max (0902)
MedScribe (Vals AI)89.4%85.0%Grok 4.7
Vals Multimodal IndexNot measured65.4%Only Qwen3.8 Max (0902) measured
Long context reasoning (AA-LCR)80.0%80.3%Qwen3.8 Max (0902)
DTBench96.0%92.0%Grok 4.7
LMCA49.4%46.2%Grok 4.7
Furniture assembly20.8%20.0%Grok 4.7
LMArena Text13991483Qwen3.8 Max (0902)
LMArena Text: instruction following14061481Qwen3.8 Max (0902)
LMArena Text: creative writing13811477Qwen3.8 Max (0902)
LMArena Vision12311313Qwen3.8 Max (0902)
LMArena Text: English14111491Qwen3.8 Max (0902)
LMArena Text: non-English13861473Qwen3.8 Max (0902)
LMArena Text: Chinese14491539Qwen3.8 Max (0902)
LMArena Text: German13661478Qwen3.8 Max (0902)
LMArena Text: Japanese13591473Qwen3.8 Max (0902)
LMArena Text: Korean13831460Qwen3.8 Max (0902)
LMArena Text: French14311498Qwen3.8 Max (0902)
LMArena Text: Spanish14061489Qwen3.8 Max (0902)
LMArena Text: Russian13991482Qwen3.8 Max (0902)
LMArena Text: Polish14201471Qwen3.8 Max (0902)
LMArena Text: multi-turn13941489Qwen3.8 Max (0902)
LMArena Text: longer queries14161488Qwen3.8 Max (0902)
LMArena Text: writing and language13941477Qwen3.8 Max (0902)
LMArena Text: entertainment and media13761464Qwen3.8 Max (0902)
LMArena Vision: English12291311Qwen3.8 Max (0902)
LMArena Vision: Chinese12501358Qwen3.8 Max (0902)
LMArena Vision: reading text12411322Qwen3.8 Max (0902)
LMArena Vision: humorNot measured1304Only Qwen3.8 Max (0902) measured
LMArena Vision: creative writing12171312Qwen3.8 Max (0902)
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Grok 4.7 and Qwen3.8 Max (0902)
BenchmarkGrok 4.7Qwen3.8 Max (0902)Leader
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 4.7$0.0050Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request

Same cost

Repository review

50K input + 3K output tokens

Grok 4.7$0.118Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request

Same cost

Agent loop

200K input + 10K output tokens

Grok 4.7$0.460Fits in one request
Qwen3.8 Max (0902)$0.460Fits in one request

Same cost

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 4.7 and Qwen3.8 Max (0902)
SpecificationSpaceXAI Grok 4.7Qwen3.8 Max (0902)
MakerxAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 21, 2026September 3, 2026
Context window500K1M
Input $/Mtok$2.00$2.00
Output $/Mtok$6.00$6.00
Coding index75.063.5
Independent measurements behind it22
Cost per solved taskNot computable$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is Grok 4.7 better than Qwen3.8 Max (0902) for coding?

Pick Grok 4.7 for coding: it scores 75.0 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902). Pick Qwen3.8 Max (0902) when the context window is larger, 1M against 500K tokens, or when what matters is LMArena WebDev or Terminal-Bench 4 (Vals AI), where it leads.

Which is cheaper, Grok 4.7 or Qwen3.8 Max (0902)?

Grok 4.7 costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.

Which has the bigger context window, Grok 4.7 or Qwen3.8 Max (0902)?

Qwen3.8 Max (0902), with 1M tokens against 500K.

How many benchmarks is the Grok 4.7 vs Qwen3.8 Max (0902) comparison based on?

89 benchmarks have a result for both models as of October 21, 2026. Grok 4.7's coding index rests on 2 independent benchmarks and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/grok-4-7-vs-qwen3-8-max-0902" title="Grok 4.7 vs Qwen3.8 Max (0902), LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/grok-4-7-vs-qwen3-8-max-0902">LLMBenchmark.ai, Grok 4.7 vs Qwen3.8 Max (0902)</a></p>