Skip to main content

Model profile

Qwen3.5-27B

AlibabaCurrentReleased Mar 4, 2026
Data verified
Overall Score
60.7Public #45 of 200Verified #34 of 99
Arena Elo
1409
Eligible category ranks
6of 8
Price (1M tokens)
$0 in / $0 out
API pricing
Speed
Not listed
Context
262K

Evidence coverage

28 of 323 tracked benchmarks are published. 14 are verified and 14 provisional. 7 of 8 categories are measured.

Updated July 23, 2026Methodology
Published / tracked
28 / 323
Verified
14
Provisional
14
Categories with evidence
7 / 8

Evidence by category

  • Agentic5 benchmarks
    Mixed evidence
  • Coding3 benchmarks
    Mixed evidence
  • Reasoning3 benchmarks
    Mixed evidence
  • Knowledge9 benchmarks
    Mixed evidence
  • Math0 benchmarks
    Not measured
  • Multilingual1 benchmark
    Verified
  • Multimodal5 benchmarks
    Mixed evidence
  • Inst. Following2 benchmarks
    Mixed evidence
Open WeightSelf-hostReasoning
Confidence:
High
base

Qwen3.5-27B ranks #45 out of 200 models on the public leaderboard with an overall score of 60.7/100. It also ranks #34 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Qwen3.5-27B is a open weight model with a 262K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

This profile currently has 28 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Instruction Following (#2), while its weakest is Agentic (#57). This performance profile makes it a well-rounded choice across a range of tasks.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 60.4260.89

  1. GPT-5.4 Pro
    OpenAI
    #4460.89
    GPT-5.4 Pro is #44 with a score of 60.89.
    Compare
  2. Qwen3.5-27BCurrent model
    Alibaba
    #4560.7
    Qwen3.5-27B is #45 with a score of 60.7.
  3. DeepSeek V4 Pro
    DeepSeek
    #4660.66
    DeepSeek V4 Pro is #46 with a score of 60.66.
    Compare
  4. Qwen3.5-122B-A10B
    Alibaba
    #4760.56
    Qwen3.5-122B-A10B is #47 with a score of 60.56.
    Compare
  5. Grok 4.1 Fast (Reasoning)
    xAI
    #4860.51
    Grok 4.1 Fast (Reasoning) is #48 with a score of 60.51.
    Compare
  6. Gemini 3 Flash
    Google
    #4960.49
    Gemini 3 Flash is #49 with a score of 60.49.
    Compare
  7. Grok 4
    xAI
    #5060.42
    Grok 4 is #50 with a score of 60.42.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

  1. Inst. Following97%
    Eligible cohort rank #2 of 31Category score 93.0
  2. Multilingual25%
    Eligible cohort rank #10 of 13Category score 36.8
  3. Knowledge69%
    Eligible cohort rank #17 of 52Category score 76.5
  4. Multimodal4%
    Eligible cohort rank #28 of 29Category score 0.0
  5. Coding74%
    Eligible cohort rank #33 of 122Category score 55.7
  6. Agentic53%
    Eligible cohort rank #57 of 119Category score 48.5

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #57 of 119Percentile 53rdWeight 22%5 benchmarksMixed sources48.5
CodingRank #33 of 122Percentile 74thWeight 20%3 benchmarksMixed sources55.7
ReasoningRank Not rankedWeight 17%3 benchmarksMixed sources77.6
KnowledgeRank #17 of 52Percentile 69thWeight 12%9 benchmarksMixed sources76.5
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualRank #10 of 13Percentile 25thWeight 7%1 benchmarkVerified36.8
MultimodalRank #28 of 29Percentile 4thWeight 12%5 benchmarksMixed sources0.0
Inst. FollowingRank #2 of 31Percentile 97thWeight 5%2 benchmarksMixed sources93.0

Chatbot Arena performance

Scroll horizontally to inspect confidence intervals and vote counts.

Chatbot Arena Elo, confidence interval, and vote count by evaluation view
ViewEloConfidence intervalVotes
Text Overall1409±4.427,308
Coding1450±7.47,522
Math1429±14.61,648
Instruction Following1401±6.98,562
Creative Writing1358±9.84,058
Multi-turn1416±9.24,592
Hard Prompts1427±5.417,030
Hard Prompts (English)1441±7.08,445
Longer Query1423±6.710,210

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic5 benchmarks
Terminal-Bench 2.0Provider exact
41.6%Weighted 38%
Source: Qwen3.5-27B model cardProvenance: Provider exact
OSWorld-VerifiedProvider exact
56.2%Weighted 34%
Source: Qwen3.5-27B model cardProvenance: Provider exact
BrowseCompProvider exact
61%Weighted 28%
Source: Qwen3.5-27B model cardProvenance: Provider exact
τ²-bench resultsReported

τ²-Bench Tool-Agent-User Evaluation

93.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Gert LabsBenchmark exact

Gert Labs Composite Game Benchmark

39.41%Display only
Source: Gert Labs rankingsProvenance: Gert Labs reports this composite leaderboard score in the public rankings API. BenchLM scales the source gscore from 0-1 to 0-100 and stores it as a display-only agentic benchmark.
Coding3 benchmarks
SWE-RebenchBenchmark exact
58.9%Weighted 20%
Source: SWE-Rebench leaderboardProvenance: Live default SWE-Rebench leaderboard lists Qwen3.5-27B at 58.9% resolved rate.
SWE-bench VerifiedProvider exact

Software Engineering Benchmark Verified

72.4%Weighted 16%
Source: Qwen3.5-27B model cardProvenance: Provider exact
AA-SciCodeReported

Artificial Analysis SciCode

39.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning3 benchmarks
LongBench v2Provider exact
60.6%Weighted 38%
Source: Qwen3.5-27B model cardProvenance: Provider exact
AA-LCRReported

Artificial Analysis Long Context Reasoning

67.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

0.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge9 benchmarks
MMLU-ProProvider exact

Massive Multitask Language Understanding Professional

86.1%Weighted 30%
Source: Qwen3.5-27B model cardProvenance: Provider exact
SuperGPQAProvider exact

SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines

65.6%Weighted 7%
Source: Qwen3.5-27B model cardProvenance: Provider exact
GPQAProvider exact

Graduate-Level Google-Proof Q&A

85.5%Weighted 7%
Source: Qwen3.5-27B model cardProvenance: Provider exact
Artificial Analysis Intelligence IndexReported
33.8%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

85.8%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

22.2%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

-42.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

21.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

79.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Multilingual1 benchmark
MMLU-ProXProvider exact
82.2%Weighted 100%
Source: Qwen3.5-27B model cardProvenance: Provider exact
Multimodal5 benchmarks
MMMUReported

Massive Multi-discipline Multimodal Understanding

82.3%Display only
Source: Reported upstream sourceProvenance: Reported row carried from an upstream public source. Displayable on BenchLM, but not treated as verified unless explicitly marked otherwise.
MMVUReported

Multimodal Multi-disciplinary Video Understanding

73.3%Display only
Source: Reported upstream sourceProvenance: Reported row carried from an upstream public source. Displayable on BenchLM, but not treated as verified unless explicitly marked otherwise.
MathVisionProvider exact
86.0%Display only
Source: Qwen3.5-122B-A10B model cardProvenance: Provider exact
V*Provider exact
93.7%Display only
Source: Qwen3.5-122B-A10B model cardProvenance: Qwen reports V* as with-CI / without-CI. BenchLM stores the first published value.
AA-MMMU-ProReported

Artificial Analysis MMMU-Pro

75.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Inst. Following2 benchmarks
IFEvalProvider exact

Instruction-Following Eval

95%Weighted 35%
Source: Qwen3.5-27B model cardProvenance: Provider exact
AA-IFBenchReported

Artificial Analysis IFBench

75.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does Qwen3.5-27B perform overall in AI benchmarks?

Qwen3.5-27B currently ranks #45 out of 200 models on BenchLM's provisional leaderboard with an overall score of 60.7. It also ranks #34 out of 99 on the verified leaderboard. It is created by Alibaba. Its published context window is 262K.

Is Qwen3.5-27B good for knowledge and understanding?

Qwen3.5-27B ranks #17 out of 52 models in knowledge and understanding benchmarks with an average score of 76.5. There are stronger options in this category.

Is Qwen3.5-27B good for coding and programming?

Qwen3.5-27B ranks #33 out of 122 models in coding and programming benchmarks with an average score of 55.7. There are stronger options in this category.

Is Qwen3.5-27B good for reasoning and logic?

Qwen3.5-27B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Qwen3.5-27B good for agentic tool use and computer tasks?

Qwen3.5-27B ranks #57 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 48.5. There are stronger options in this category.

Is Qwen3.5-27B good for multimodal and grounded tasks?

Qwen3.5-27B ranks #28 out of 29 models in multimodal and grounded tasks benchmarks with an average score of 0. There are stronger options in this category.

Is Qwen3.5-27B good for instruction following?

Qwen3.5-27B ranks #2 out of 31 models in instruction following benchmarks with an average score of 93. It is among the top performers in this category.

Is Qwen3.5-27B good for multilingual tasks?

Qwen3.5-27B ranks #10 out of 13 models in multilingual tasks benchmarks with an average score of 36.8. It is among the top performers in this category.

Is Qwen3.5-27B open source?

Yes, Qwen3.5-27B is an open weight model created by Alibaba, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Does Qwen3.5-27B have full benchmark coverage on BenchLM?

Not yet. Qwen3.5-27B currently has 28 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Qwen3.5-27B?

Qwen3.5-27B has a published context window of 262K, which determines how much text it can process in a single interaction.

Last updated: July 23, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

Choose with this week’s evidence

Join 2,000+ readers for ranking moves, new releases, pricing changes, and the evidence behind them.

Free. One email per week.