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Grok 4.20 vs Qwen3.8 27B

Qwen3.8 27B leads Grok 4.20 on coding, 74.2 to 33.3 on the Vibe Coding Index, at about the same output price ($2.55 vs $2.50 per million). Updated October 22, 2026; 27 benchmarks have a result for both.

Grok 4.20xAI
Coding
33.3
Overall
41.0
Output $/M
$2.50
10
Qwen3.8 27BQwen
Coding
74.2
Overall
59.6
Output $/M
$2.55
17
vs boards won of 27 shared

Grok 4.20 or Qwen3.8 27B: which to pick

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 33.3 for Grok 4.20.

Pick Grok 4.20 for output tokens 1.0x cheaper ($2.50 vs $2.55 per million) and a lower cost per solved task ($0.72 against $1.26).

Shared results
27
Grok 4.20 only
28
Qwen3.8 27B only
58
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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 4.20 33.3 from 2 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
Widest category
Agentic work, 28.5 points apart on average over 4 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Grok 4.20 4.1% against Qwen3.8 27B 64.8%, 60.8 points apart on a 0 to 100 scale.
Output price
Grok 4.20 $2.50 against Qwen3.8 27B $2.55 per million output tokens, 1.0x apart.
Context window
Grok 4.20 takes 2M tokens, Qwen3.8 27B 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 4.20BarsQwen3.8 27BTies
Coding14
Intelligence11
Agentic work04
Reasoning42
Knowledge32
General14
All shared boards1017
CodingLike-for-likeSix of these boards feed the Vibe Coding Index14
Coding benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDevNot measured1593Only Qwen3.8 27B measured
AA Coding IndexNot measured68.1Only Qwen3.8 27B measured
LiveCodeBench (Vals AI)84.3%84.0%Grok 4.20
SWE-bench Verified (Vals AI)72.2%86.0%Qwen3.8 27B
Vibe Code Bench (Vals AI)4.1%64.8%Qwen3.8 27B
Code migration (Vals AI)0.3%14.2%Qwen3.8 27B
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)44.2%58.4%Qwen3.8 27B
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
SciCodeNot measured46.6%Only Qwen3.8 27B measured
Terminal-Bench Hard (Artificial Analysis run)37.9%Not measuredOnly Grok 4.20 measured
Terminal-Bench57.3%Not measuredOnly Grok 4.20 measured
WeirdML52.3%Not measuredOnly Grok 4.20 measured
LMArena Text: codingNot measured1483Only Qwen3.8 27B measured
LMArena Text: software and ITNot measured1478Only Qwen3.8 27B measured
LMArena WebDev: ReactNot measured1602Only Qwen3.8 27B measured
LMArena WebDev: HTMLNot measured1570Only Qwen3.8 27B measured
LMArena WebDev: from an imageNot measured1577Only Qwen3.8 27B measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
AA Intelligence Index25.733.7Qwen3.8 27B
Epoch Capabilities Index152.1151.7Grok 4.20
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
Agentic work benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
AA Agentic IndexNot measured45.8Only Qwen3.8 27B measured
Design Arena: agents building web apps1144Not measuredOnly Grok 4.20 measured
Design Arena: agents building full-stack apps1054Not measuredOnly Grok 4.20 measured
Design Arena: agents building mobile apps1090Not measuredOnly Grok 4.20 measured
Design Arena: agents building Android apps1045Not measuredOnly Grok 4.20 measured
Design Arena: agents building Godot games1089Not measuredOnly Grok 4.20 measured
Design Arena: HTML slides1180Not measuredOnly Grok 4.20 measured
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)28.5%48.5%Qwen3.8 27B
Tax Agent Bench (Vals AI)7.0%30.9%Qwen3.8 27B
Legal Research Bench (Vals AI)13.9%36.1%Qwen3.8 27B
Excel Modeling Benchmark (Vals AI)11.7%59.7%Qwen3.8 27B
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
τ²-Bench Telecom93.0%Not measuredOnly Grok 4.20 measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
Vending-Bench 2$4,663Not measuredOnly Grok 4.20 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index42
Reasoning benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
GPQA Diamond88.6%88.9%Qwen3.8 27B
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)83.5%83.9%Qwen3.8 27B
GPQA Diamond (Artificial Analysis run)91.1%90.5%Grok 4.20
Humanity's Last Exam (Artificial Analysis run)34.5%33.9%Grok 4.20
ARC-AGI89.5%87.5%Grok 4.20
ARC-AGI-265.1%42.4%Grok 4.20
LMArena Text: hard promptsNot measured1459Only Qwen3.8 27B measured
LMArena Text: expertNot measured1479Only Qwen3.8 27B measured
LMArena Text: hard prompts in EnglishNot measured1461Only Qwen3.8 27B measured
LMArena Vision: diagramsNot measured1285Only Qwen3.8 27B measured
LMArena Vision: homeworkNot measured1295Only Qwen3.8 27B measured
Kagi LLM Benchmark75.0%Not measuredOnly Grok 4.20 measured
Neither model has a result on the other 9 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
AIME96.5%Not measuredOnly Grok 4.20 measured
ProofBenchNot measured16.0%Only Qwen3.8 27B measured
LMArena Text: mathNot measured1455Only Qwen3.8 27B measured
LMArena Text: mathematical workNot measured1458Only Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
Knowledge benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
MMLU Pro86.3%84.3%Grok 4.20
LegalBench (Vals AI)77.7%82.4%Qwen3.8 27B
CaseLaw (Vals AI)54.4%Not measuredOnly Grok 4.20 measured
CorpFin (Vals AI)63.7%Not measuredOnly Grok 4.20 measured
TaxEval (Vals AI)74.1%70.8%Grok 4.20
MortgageTax (Vals AI)45.4%64.9%Qwen3.8 27B
MedQA (Vals AI)94.5%Not measuredOnly Grok 4.20 measured
MedCode (Vals AI)32.2%28.7%Grok 4.20
LMArena Text: scienceNot measured1467Only Qwen3.8 27B measured
LMArena Text: medicine and healthcareNot measured1437Only Qwen3.8 27B measured
LMArena Text: legal and governmentNot measured1447Only Qwen3.8 27B measured
LMArena Text: business and financeNot measured1438Only Qwen3.8 27B measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
Design Arena: websites1229Not measuredOnly Grok 4.20 measured
Design Arena: UI components1200Not measuredOnly Grok 4.20 measured
Design Arena: game dev1193Not measuredOnly Grok 4.20 measured
Design Arena: data viz1217Not measuredOnly Grok 4.20 measured
Design Arena: 3D1193Not measuredOnly Grok 4.20 measured
Design Arena: all code categories1221Not measuredOnly Grok 4.20 measured
Design Arena: SVG1165Not measuredOnly Grok 4.20 measured
Design Arena: ASCII art1175Not measuredOnly Grok 4.20 measured
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index14
General benchmarks for Grok 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)38.2%52.4%Qwen3.8 27B
MedScribe (Vals AI)63.4%83.8%Qwen3.8 27B
Vals Multimodal Index39.1%Not measuredOnly Grok 4.20 measured
IFBench81.2%Not measuredOnly Grok 4.20 measured
Long context reasoning (AA-LCR)69.0%82.0%Qwen3.8 27B
DTBench90.1%88.0%Grok 4.20
LMCA38.7%41.4%Qwen3.8 27B
CL-bench22.2%Not measuredOnly Grok 4.20 measured
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
CL-bench Life11.9%Not measuredOnly Grok 4.20 measured
LMArena TextNot measured1440Only Qwen3.8 27B measured
LMArena Text: instruction followingNot measured1436Only Qwen3.8 27B measured
LMArena Text: creative writingNot measured1383Only Qwen3.8 27B measured
LMArena VisionNot measured1269Only Qwen3.8 27B measured
LMArena Text: EnglishNot measured1448Only Qwen3.8 27B measured
LMArena Text: non-EnglishNot measured1428Only Qwen3.8 27B measured
LMArena Text: ChineseNot measured1501Only Qwen3.8 27B measured
LMArena Text: GermanNot measured1443Only Qwen3.8 27B measured
LMArena Text: JapaneseNot measured1387Only Qwen3.8 27B measured
LMArena Text: KoreanNot measured1384Only Qwen3.8 27B measured
LMArena Text: FrenchNot measured1465Only Qwen3.8 27B measured
LMArena Text: SpanishNot measured1449Only Qwen3.8 27B measured
LMArena Text: RussianNot measured1415Only Qwen3.8 27B measured
LMArena Text: PolishNot measured1439Only Qwen3.8 27B measured
LMArena Text: multi-turnNot measured1440Only Qwen3.8 27B measured
LMArena Text: longer queriesNot measured1448Only Qwen3.8 27B measured
LMArena Text: writing and languageNot measured1405Only Qwen3.8 27B measured
LMArena Text: entertainment and mediaNot measured1393Only Qwen3.8 27B measured
LMArena Vision: EnglishNot measured1267Only Qwen3.8 27B measured
LMArena Vision: ChineseNot measured1326Only Qwen3.8 27B measured
LMArena Vision: reading textNot measured1281Only Qwen3.8 27B measured
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writingNot measured1237Only Qwen3.8 27B 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 4.20 and Qwen3.8 27B
BenchmarkGrok 4.20Qwen3.8 27BLeader
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 4.20$0.0025Fits in one request
Qwen3.8 27B$0.0017Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

Grok 4.20$0.070Fits in one request
Qwen3.8 27B$0.029Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

Grok 4.20$0.275Fits in one request
Qwen3.8 27B$0.111Fits in one request

Qwen3.8 27B 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 4.20 and Qwen3.8 27B
SpecificationSpaceXAI Grok 4.20Qwen3.8 27B
MakerxAIQwen
WeightsNo public weights listedOpen weights
ReleasedMarch 31, 2026August 14, 2026
Context window2M1M
Input $/Mtok$1.25$0.425
Output $/Mtok$2.50$2.55
Coding index33.374.2
Independent measurements behind it24
Cost per solved task$0.72$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is Grok 4.20 better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 33.3 for Grok 4.20. Pick Grok 4.20 for output tokens 1.0x cheaper ($2.50 vs $2.55 per million) and a lower cost per solved task ($0.72 against $1.26).

Which is cheaper, Grok 4.20 or Qwen3.8 27B?

Grok 4.20 costs $1.25 per million input tokens and $2.50 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Per solved SWE-bench Verified task, Grok 4.20 costs $0.72 and Qwen3.8 27B $1.26.

Which has the bigger context window, Grok 4.20 or Qwen3.8 27B?

Grok 4.20, with 2M tokens against 1M.

How many benchmarks is the Grok 4.20 vs Qwen3.8 27B comparison based on?

27 benchmarks have a result for both models as of October 22, 2026. Grok 4.20's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/grok-4-20-vs-qwen3-8-27b">LLMBenchmark.ai, Grok 4.20 vs Qwen3.8 27B</a></p>