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Model comparison

Grok 4.20 vs Qwen3.5 397B

Data verified

Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

53.88/100
Margin
2.3pts
winning →
56.19/100
1 category wins3 category wins

Public leaderboard positions: Grok 4.20 #93 (Estimated); Qwen3.5 397B #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Grok 4.20 and Qwen3.5 397B share 6 comparable benchmark results. 4 of 8 categories are comparable. 13 results are unique to Grok 4.20; 49 to Qwen3.5 397B.

Updated July 28, 2026
Shared results
6
Grok 4.20 only
13
Qwen3.5 397B only
49
Comparable categories
4 / 8

Pick Qwen3.5 397B if you want the stronger benchmark profile. Grok 4.20 only becomes the better choice if coding is the priority or you need the larger 2M context window.

Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 3 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Qwen3.5 397B has the cleaner BenchAlign overall profile here, landing at 56.19 versus 53.88. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Qwen3.5 397B's sharpest advantage is in reasoning, where it averages 63.2 against 53.3. The single biggest benchmark swing on the page is CharXiv, 60.9% to 80.8%. Grok 4.20 does hit back in coding, so the answer changes if that is the part of the workload you care about most.

Grok 4.20 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. Grok 4.20 is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Grok 4.20 gives you the larger context window at 2M, compared with 128K for Qwen3.5 397B.

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 Grok 4.20 and Qwen3.5 397B
CategoryGrok 4.20ΔQwen3.5 397B
ReasoningGrok 4.2053.3Margin→ 9.9Qwen3.5 397B63.2
MultimodalGrok 4.2070.1Margin→ 9.5Qwen3.5 397B79.6
AgenticGrok 4.2047.1Margin→ 9.4Qwen3.5 397B56.5
CodingGrok 4.2067.1Margin← 0.6Qwen3.5 397B66.5
KnowledgeGrok 4.20Not measuredMarginNo overlapQwen3.5 397B56.6
MathGrok 4.20Not measuredMarginNo overlapQwen3.5 397B90.6
MultilingualGrok 4.20Not measuredMarginNo overlapQwen3.5 397B84.7
Inst. FollowingGrok 4.20Not measuredMarginNo overlapQwen3.5 397B92.6

Decisive benchmark drivers

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

More
A · Grok 4.20B · Qwen3.5 397B

  1. CharXiv

    Multimodal
    Source ↗
    A 60.9%B 80.8%
    Winner: Qwen3.5 397BΔ 19.9
    CharXiv: Grok 4.20 scored 60.9%; Qwen3.5 397B scored 80.8%. Qwen3.5 397B wins this benchmark.

  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 47.1%B 52.5%
    Winner: Qwen3.5 397BΔ 5.4
    Terminal-Bench 2.0: Grok 4.20 scored 47.1%; Qwen3.5 397B scored 52.5%. Qwen3.5 397B wins this benchmark.

  3. MMMU-Pro

    Multimodal
    Source ↗
    A 75.2%B 79%
    Winner: Qwen3.5 397BΔ 3.8
    MMMU-Pro: Grok 4.20 scored 75.2%; Qwen3.5 397B scored 79%. Qwen3.5 397B wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 51.8%B 50.9%
    Winner: Grok 4.20Δ 0.9
    SWE-bench Pro: Grok 4.20 scored 51.8%; Qwen3.5 397B scored 50.9%. Grok 4.20 wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 76.7%B 76.2%
    Winner: Grok 4.20Δ 0.5
    SWE-bench Verified: Grok 4.20 scored 76.7%; Qwen3.5 397B scored 76.2%. Grok 4.20 wins this benchmark.

Operational comparison

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

MetricGrok 4.20Qwen3.5 397BComparison
Input / output priceUSD per 1M tokensGrok 4.20$2 input / $6 outputQwen3.5 397B$0.6 input / $3.6 outputQwen3.5 397B has the lower combined listed price.
Generation speedtokens per secondGrok 4.20233 tok/sQwen3.5 397B96 tok/sGrok 4.20 has the higher measured throughput.
First-answer latencyseconds to first tokenGrok 4.2010.33 sQwen3.5 397B2.44 sQwen3.5 397B reaches the first token sooner.
Context windowmaximum listed tokensGrok 4.202MQwen3.5 397B128KGrok 4.20 lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.5 397B wins
BenchmarkGrok 4.20Qwen3.5 397BResult
Terminal-Bench 2.0Source 47.1%52.5%Qwen3.5 397B leads
DeepSearchQASource 62.8%—Not comparable
Gert LabsSource 38.36%46.76%Qwen3.5 397B leads
BrowseCompSource —62%Not comparable
Claw-EvalSource —56.8%Not comparable
QwenClawBenchSource —51.8%Not comparable
τ³-bench resultsSource —68.4%Not comparable
VITA-BenchSource —43.7%Not comparable
DeepPlanningSource —37.6%Not comparable
ToolathlonSource —36.3%Not comparable
MCP AtlasSource —46.1%Not comparable
MCP-TasksSource —74.2%Not comparable
WideResearchSource —74.0%Not comparable
τ²-bench resultsSource —95.6%Not comparable
ResearchClawBenchSource —14.2%Not comparable
AA Agentic IndexSource —19.9%Not comparable
APEX-Agents-AASource —15.3%Not comparable
GDPval-AASource —23.1%Not comparable
GDPval-AASource —962Not comparable
CodingGrok 4.20 wins
BenchmarkGrok 4.20Qwen3.5 397BResult
LiveCodeBench ProSource 74.2%—Not comparable
SWE-bench VerifiedSource 76.7%76.2%Grok 4.20 leads
SWE-bench ProSource 51.8%50.9%Grok 4.20 leads
Vibe Code BenchSource 4.06%—Not comparable
LiveCodeBench v6Source —83.6%Not comparable
AA-SciCodeSource —42.0%Not comparable
AA Coding IndexSource —48.2%Not comparable
ReasoningQwen3.5 397B wins
BenchmarkGrok 4.20Qwen3.5 397BResult
ARC-AGI-2Source 53.3%—Not comparable
ARC-AGI-3Source 0.1%—Not comparable
LongBench v2Source —63.2%Not comparable
AI-NeedleSource —68.7%Not comparable
AA-LCRSource —65.7%Not comparable
CritPtSource —1.7%Not comparable
Knowledge
BenchmarkGrok 4.20Qwen3.5 397BResult
GPQA-DSource 88.5%—Not comparable
HLE w/o toolsSource 31.6%—Not comparable
HealthBench HardSource 20.3%—Not comparable
MedXpertQA (Text)Source 50.2%—Not comparable
GPQASource —88.4%Not comparable
SuperGPQASource —70.4%Not comparable
MMLU-ProSource —87.8%Not comparable
MMLU-ReduxSource —94.9%Not comparable
C-EvalSource —93%Not comparable
HLESource —28.7%Not comparable
Artificial Analysis Intelligence IndexSource —33.7%Not comparable
AA-GPQA DiamondSource —89.3%Not comparable
AA-HLESource —27.3%Not comparable
AA-Omniscience IndexSource —-29.8%Not comparable
AA-Omniscience AccuracySource —31.4%Not comparable
AA-Omniscience Hallucination RateSource —89.1%Not comparable
Math
BenchmarkGrok 4.20Qwen3.5 397BResult
AIME26Source —93.3%Not comparable
HMMT Feb 2025Source —94.8%Not comparable
HMMT Nov 2025Source —92.7%Not comparable
HMMT Feb 2026Source —87.9%Not comparable
MMAnswerBenchSource —80.9%Not comparable
Multilingual
BenchmarkGrok 4.20Qwen3.5 397BResult
MMLU-ProXSource —84.7%Not comparable
NOVA-63Source —59.1%Not comparable
MultimodalQwen3.5 397B wins
BenchmarkGrok 4.20Qwen3.5 397BResult
MMMU-ProSource 75.2%79%Qwen3.5 397B leads
CharXivSource 60.9%80.8%Qwen3.5 397B leads
ERQASource 54.1%—Not comparable
SimpleVQASource 57.4%—Not comparable
MedXpertQA (MM)Source 65.8%—Not comparable
Design Arena WebsiteSource 1252—Not comparable
MathVisionSource —88.6%Not comparable
VideoMMMUSource —84.7%Not comparable
ScreenSpot ProSource —65.6%Not comparable
V*Source —95.8%Not comparable
AA-MMMU-ProSource —77.3%Not comparable
Inst. Following
BenchmarkGrok 4.20Qwen3.5 397BResult
IFEvalSource —92.6%Not comparable
AA-IFBenchSource —78.8%Not comparable
Frequently Asked Questions (5)

Which is better, Grok 4.20 or Qwen3.5 397B?

Qwen3.5 397B is ahead on BenchLM's BenchAlign leaderboard, 56.19 to 53.88. The biggest single separator in this matchup is CharXiv, where the scores are 60.9% and 80.8%.

Which is better for coding, Grok 4.20 or Qwen3.5 397B?

Grok 4.20 has the edge for coding in this comparison, averaging 67.1 versus 66.5. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.

Which is better for reasoning, Grok 4.20 or Qwen3.5 397B?

Qwen3.5 397B has the edge for reasoning in this comparison, averaging 63.2 versus 53.3. Grok 4.20 stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, Grok 4.20 or Qwen3.5 397B?

Qwen3.5 397B has the edge for agentic tasks in this comparison, averaging 56.5 versus 47.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Grok 4.20 or Qwen3.5 397B?

Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 70.1. Inside this category, CharXiv is the benchmark that creates the most daylight between them.

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