Grok 4.20 vs Qwen3.6 Plus

Updated October 27, 2026. Rank says Grok 4.20 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Grok 4.20 has the higher public point estimate, 57.6 versus 53.73. Their conditional score ranges overlap. These ranges do not establish rank confidence. 12 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Grok 4.20

xAI

57.6/100

Estimated · Public rank #63

Conditional range 47.9–67.3

Model B

Qwen3.6 Plus

Alibaba

53.73/100

Supported · Public rank #82

90% interval 44.1–63.4

Shared results: 12
Grok 4.20 only: 12
Qwen3.6 Plus only: 37
Like-for-like categories: 4 / 8

Estimated: Grok 4.20 · Supported: Qwen3.6 Plus. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Coding work
Code generation, repair, and software-engineering tasks
Qwen3.6 Plus
Qwen3.6 Plus has the higher public coding point estimate, 40.3 to 21.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.6 Plus
Qwen3.6 Plus has the higher public agentic point estimate, 34.9 to 25.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited

Show secondary and unsupported calls

Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

21.8Grok 4.2040.3Qwen3.6 Plus

Like-for-like · BenchAlign v5.8

Qwen3.6 Plus has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

CharXivMultimodal
Normalized gap 20.6
Grok 4.20:60.9%
Qwen3.6 Plus:81.5%
Grok 4.20 source Qwen3.6 Plus source
Terminal-Bench 2.0Agentic
Normalized gap 14.5
Grok 4.20:47.1%
Qwen3.6 Plus:61.6%
Grok 4.20 source Qwen3.6 Plus source
SWE-bench ProCoding
Normalized gap 4.8
Grok 4.20:51.8%
Qwen3.6 Plus:56.6%
Grok 4.20 source Qwen3.6 Plus source
MMMU-ProMultimodal
Normalized gap 3.6
Grok 4.20:75.2%
Qwen3.6 Plus:78.8%
Grok 4.20 source Qwen3.6 Plus source
SWE-bench VerifiedCoding
Normalized gap 2.1
Grok 4.20:76.7%
Qwen3.6 Plus:78.8%
Grok 4.20 source Qwen3.6 Plus source

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like

Grok 4.20: 25.6; Supported · #109/134
Qwen3.6 Plus: 34.9; Supported · #87/134
Basis: BenchAlign v5.8 lane · 5 vs 13 public rows
Reading: Qwen3.6 Plus leads · intervals overlap

Coding

Like-for-like

Grok 4.20: 21.8; Supported · #122/155
Qwen3.6 Plus: 40.3; Supported · #69/155
Basis: BenchAlign v5.8 lane · 6 vs 9 public rows
Reading: Qwen3.6 Plus leads

Multimodal

Like-for-like

Grok 4.20: 54.3; #50/58
Qwen3.6 Plus: 75.9; #24/58
Basis: Provisional lane · 2 vs 2 weighted rows
Reading: Qwen3.6 Plus leads

Knowledge

Like-for-like

Grok 4.20: 52.8; Supported · #72/189
Qwen3.6 Plus: 53.2; Supported · #69/189
Basis: BenchAlign v5.8 lane · 6 vs 8 public rows
Reading: Practical tie

Reasoning

Not comparable

Grok 4.20: 44.9; Unranked · 2 rankable rows
Qwen3.6 Plus: 73.9; Unranked · 4 rankable rows
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Grok 4.20: Not ranked
Qwen3.6 Plus: 93.8; #4/17
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Grok 4.20: Not ranked
Qwen3.6 Plus: 85.8; #50/156
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Grok 4.20: Not ranked
Qwen3.6 Plus: 69.5; #6/12
Basis: Provisional lane · 0 vs 3 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Grok 4.20 and Qwen3.6 Plus
Category	Grok 4.20	Qwen3.6 Plus	Basis	Reading
Agentic	25.6Supported · #109/134	34.9Supported · #87/134	Like-for-likeBenchAlign v5.8 lane · 5 vs 13 public rows	Qwen3.6 Plus leads · intervals overlap
Coding	21.8Supported · #122/155	40.3Supported · #69/155	Like-for-likeBenchAlign v5.8 lane · 6 vs 9 public rows	Qwen3.6 Plus leads
Multimodal	54.3#50/58	75.9#24/58	Like-for-likeProvisional lane · 2 vs 2 weighted rows	Qwen3.6 Plus leads
Knowledge	52.8Supported · #72/189	53.2Supported · #69/189	Like-for-likeBenchAlign v5.8 lane · 6 vs 8 public rows	Practical tie
Reasoning	44.9Unranked · 2 rankable rows	73.9Unranked · 4 rankable rows	Not comparableProvisional lane · 2 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	93.8#4/17	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Instruction following	Not ranked	85.8#50/156	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	69.5#6/12	Not comparableProvisional lane · 0 vs 3 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Grok 4.20: $0.0025; Fits in one request
Qwen3.6 Plus: API rate not published; Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Grok 4.20: $0.07; Fits in one request
Qwen3.6 Plus: API rate not published; Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Grok 4.20: $0.09; Fits in one request
Qwen3.6 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Qwen3.6 Plus has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationGrok 4.20Qwen3.6 Plus

Context window

Maximum documented context; output-token limits may be lower.

Grok 4.20

Qwen3.6 Plus

API model ID

Grok 4.20

Not sourced

Qwen3.6 Plus

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Grok 4.20

$0.2 per 1M cached input tokens

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

Grok 4.20

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

Grok 4.20

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

Grok 4.20

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

Grok 4.20

Reasoning

Qwen3.6 Plus

Reasoning

Weight access

Grok 4.20

Proprietary

Qwen3.6 Plus

Proprietary

License

Grok 4.20

Proprietary

Qwen3.6 Plus

Proprietary

Release date

Grok 4.20

2026-03-10

Qwen3.6 Plus

2026-04-02

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: Grok 4.20 has the higher public point estimate, 57.6 versus 53.73. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Grok 4.20 or Qwen3.6 Plus?

Grok 4.20 has the higher public point estimate, 57.6 versus 53.73. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Grok 4.20 or Qwen3.6 Plus?

Qwen3.6 Plus has the higher public coding point estimate, 40.3 to 21.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Grok 4.20 or Qwen3.6 Plus?

Qwen3.6 Plus has the higher public agentic tasks point estimate, 34.9 to 25.6, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Grok 4.20 or Qwen3.6 Plus?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Grok 4.20 or Qwen3.6 Plus?

Both models list the same context window, 1M.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence61 rows

Agentic

Terminal-Bench 2.0
Grok 4.2047.1%
Source
Qwen3.6 Plus61.6%
Source
Qwen3.6 Plus leads this result
DeepSearchQA
Grok 4.2062.8%
Source
Qwen3.6 Plus—
Not directly comparable
Gert Labs
Shared source
Grok 4.2038.36%
Qwen3.6 Plus50.60%
Qwen3.6 Plus leads this result
Terminal-Bench 2.1 (Vals)
Grok 4.2044.2%
Source
Qwen3.6 Plus53.2%
Source
Qwen3.6 Plus leads this result
MazeBench
Grok 4.200%
Source
Qwen3.6 Plus—
Not directly comparable
Claw-Eval
Grok 4.20—
Qwen3.6 Plus58.8%
Source
Not directly comparable
QwenClawBench
Grok 4.20—
Qwen3.6 Plus57.2%
Source
Not directly comparable
τ³-bench results
Grok 4.20—
Qwen3.6 Plus70.7%
Source
Not directly comparable
VITA-Bench
Grok 4.20—
Qwen3.6 Plus44.3%
Source
Not directly comparable
DeepPlanning
Grok 4.20—
Qwen3.6 Plus41.5%
Source
Not directly comparable
Toolathlon
Grok 4.20—
Qwen3.6 Plus39.8%
Source
Not directly comparable
MCP Atlas
Grok 4.20—
Qwen3.6 Plus48.2%
Source
Not directly comparable
MCP-Tasks
Grok 4.20—
Qwen3.6 Plus74.1%
Source
Not directly comparable
WideResearch
Grok 4.20—
Qwen3.6 Plus74.3%
Source
Not directly comparable
ResearchClawBench
Grok 4.20—
Qwen3.6 Plus18.0%
Source
Not directly comparable

Coding

LiveCodeBench Pro
Grok 4.2074.2%
Source
Qwen3.6 Plus—
Not directly comparable
SWE-bench Verified
Grok 4.2076.7%
Source
Qwen3.6 Plus78.8%
Source
Qwen3.6 Plus leads this result
SWE-bench Pro
Grok 4.2051.8%
Source
Qwen3.6 Plus56.6%
Source
Qwen3.6 Plus leads this result
Vibe Code Bench
Shared source
Grok 4.204.06%
Qwen3.6 Plus25.56%
Qwen3.6 Plus leads this result
LiveCodeBench (Vals)
Grok 4.2084.3%
Source
Qwen3.6 Plus86.0%
Source
Qwen3.6 Plus leads this result
SWE-bench (Vals)
Grok 4.2072.2%
Source
Qwen3.6 Plus73.4%
Source
Qwen3.6 Plus leads this result
SWE Multilingual
Grok 4.20—
Qwen3.6 Plus73.8%
Source
Not directly comparable
LiveCodeBench v6
Grok 4.20—
Qwen3.6 Plus87.1%
Source
Not directly comparable
NL2Repo
Grok 4.20—
Qwen3.6 Plus37.9%
Source
Not directly comparable
Terminal-Bench 2.0
Grok 4.20—
Qwen3.6 Plus61.6%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Grok 4.2053.3%
Source
Qwen3.6 Plus—
Not directly comparable
ARC-AGI-3
Grok 4.200.1%
Source
Qwen3.6 Plus—
Not directly comparable
AI-Needle
Grok 4.20—
Qwen3.6 Plus68.3%
Source
Not directly comparable
LongBench v2
Grok 4.20—
Qwen3.6 Plus62%
Source
Not directly comparable

Multimodal

MMMU-Pro
Grok 4.2075.2%
Source
Qwen3.6 Plus78.8%
Source
Qwen3.6 Plus leads this result
CharXiv
Grok 4.2060.9%
Source
Qwen3.6 Plus81.5%
Source
Qwen3.6 Plus leads this result
ERQA
Grok 4.2054.1%
Source
Qwen3.6 Plus—
Not directly comparable
SimpleVQA
Grok 4.2057.4%
Source
Qwen3.6 Plus—
Not directly comparable
MedXpertQA (MM)
Grok 4.2065.8%
Source
Qwen3.6 Plus—
Not directly comparable
MMMU
Grok 4.20—
Qwen3.6 Plus86.0%
Source
Not directly comparable
MathVision
Grok 4.20—
Qwen3.6 Plus88.0%
Source
Not directly comparable
VideoMMMU
Grok 4.20—
Qwen3.6 Plus84.0%
Source
Not directly comparable
ScreenSpot Pro
Grok 4.20—
Qwen3.6 Plus68.2%
Source
Not directly comparable
V*
Grok 4.20—
Qwen3.6 Plus96.9%
Source
Not directly comparable

Knowledge

GPQA-D
Grok 4.2088.5%
Source
Qwen3.6 Plus—
Not directly comparable
HLE w/o tools
Grok 4.2031.6%
Source
Qwen3.6 Plus—
Not directly comparable
HealthBench Hard
Grok 4.2020.3%
Source
Qwen3.6 Plus—
Not directly comparable
MedXpertQA (Text)
Grok 4.2050.2%
Source
Qwen3.6 Plus—
Not directly comparable
GPQA Diamond (Vals)
Grok 4.2088.6%
Source
Qwen3.6 Plus87.4%
Source
Grok 4.20 leads this result
MMLU-Pro (Vals)
Grok 4.2086.3%
Source
Qwen3.6 Plus87.7%
Source
Qwen3.6 Plus leads this result
GPQA
Grok 4.20—
Qwen3.6 Plus90.4%
Source
Not directly comparable
SuperGPQA
Grok 4.20—
Qwen3.6 Plus71.6%
Source
Not directly comparable
MMLU-Pro
Grok 4.20—
Qwen3.6 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Grok 4.20—
Qwen3.6 Plus94.5%
Source
Not directly comparable
C-Eval
Grok 4.20—
Qwen3.6 Plus93.3%
Source
Not directly comparable
HLE
Grok 4.20—
Qwen3.6 Plus28.8%
Source
Not directly comparable

Multilingual

MMLU-ProX
Grok 4.20—
Qwen3.6 Plus84.7%
Source
Not directly comparable
NOVA-63
Grok 4.20—
Qwen3.6 Plus57.9%
Source
Not directly comparable

Instruction following

IFEval
Grok 4.20—
Qwen3.6 Plus94.3%
Source
Not directly comparable
IFBench
Grok 4.20—
Qwen3.6 Plus75.8%
Source
Not directly comparable

Math

AIME26
Grok 4.20—
Qwen3.6 Plus95.3%
Source
Not directly comparable
HMMT Feb 2025
Grok 4.20—
Qwen3.6 Plus96.7%
Source
Not directly comparable
HMMT Nov 2025
Grok 4.20—
Qwen3.6 Plus94.6%
Source
Not directly comparable
HMMT Feb 2026
Grok 4.20—
Qwen3.6 Plus87.8%
Source
Not directly comparable
MMAnswerBench
Grok 4.20—
Qwen3.6 Plus83.8%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Grok 4.20—
Qwen3.6 Plus38.246%
Source
Not directly comparable

61 public results · 12 shared

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Last updated October 27, 2026

Grok 4.20 vs Qwen3.6 Plus

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Multimodal

Knowledge

Reasoning

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Grok 4.20 or Qwen3.6 Plus?

Which is better for coding, Grok 4.20 or Qwen3.6 Plus?

Which is better for agentic tasks, Grok 4.20 or Qwen3.6 Plus?

Which costs less, Grok 4.20 or Qwen3.6 Plus?

Which has the larger context window, Grok 4.20 or Qwen3.6 Plus?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Grok 4.20 vs Qwen3.6 Plus