Skip to main content
Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

See the free Radar Brief
Google logo
Model A
Gemini 3 Pro

Google

67.24/100

Supported · Public rank #33

90% interval 58.476.0

Gemini 3 Pro vs Qwen3.6-27B

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Alibaba logo
Model B
Qwen3.6-27B

Alibaba

52.73/100

Estimated · Public rank #120

90% interval 47.058.5

Decision reading

Gemini 3 Pro has the higher public score estimate, 67.24 versus 52.73, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Share or export

Share on XLinkedInSocial cardCSVJSON

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.

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3 Pro

    Gemini 3 Pro has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Gemini 3 Pro is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • 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: rate-fallback

  • 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

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
5
Gemini 3 Pro only
7
Qwen3.6-27B only
33
Like-for-like categories
1 / 8

4 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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.

Multimodal

Like-for-like
Gemini 3 Pro
73.4
#17/48
Qwen3.6-27B
51.5
#35/48
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Gemini 3 Pro leads

Agentic

Directional only
Gemini 3 Pro
59.6
Estimated · #30/151
Qwen3.6-27B
33.9
Supported · #133/151
Basis
BenchAlign lane · 2 vs 6 public rows
Reading
Directional only

Coding

Directional only
Gemini 3 Pro
60.9
Estimated · #21/183
Qwen3.6-27B
42.6
Supported · #128/183
Basis
BenchAlign lane · 1 vs 6 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3 Pro
65.3
Estimated · #25/181
Qwen3.6-27B
49.0
Estimated · #95/181
Basis
BenchAlign lane · 0 vs 6 public rows
Reading
Directional only

Instruction following

Directional only
Gemini 3 Pro
85.8
#38/120
Qwen3.6-27B
82.2
#50/120
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3 Pro
36.8
Unranked · 3 rankable rows
Qwen3.6-27B
73.7
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3 Pro
55.4
Unranked · 2 rankable rows
Qwen3.6-27B
72.8
Unranked · 5 rankable rows
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3 Pro
Not ranked
Qwen3.6-27B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

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

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.

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

Gemini 3 Pro
$0.008
Fits in one request
Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.6-27B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Gemini 3 Pro
$0.136
Fits in one request
Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.6-27B has no comparable published API token rate.

Cache-heavy agent loop

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

Gemini 3 Pro
$0.56
Fits in one request
Cached input priced at the published list-input rate
Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6-27B has no comparable published API token rate.

Specification differences

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

Context window

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

Gemini 3 Pro

2M

Qwen3.6-27B

262K

API model ID

Gemini 3 Pro

Not sourced

Qwen3.6-27B

Not sourced

Cached-input rate

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

Gemini 3 Pro

Not published

Qwen3.6-27B

No comparable hosted API rate

Documented inputs

Gemini 3 Pro

Not sourced

Qwen3.6-27B

Not sourced

Documented outputs

Gemini 3 Pro

Not sourced

Qwen3.6-27B

Not sourced

Provider availability

Gemini 3 Pro

Not sourced

Qwen3.6-27B

Not sourced

Reasoning profile

Gemini 3 Pro

Non-Reasoning

Qwen3.6-27B

Reasoning

Weight access

Gemini 3 Pro

Proprietary

Qwen3.6-27B

Open Weight

License

Gemini 3 Pro

Proprietary

Qwen3.6-27B

Open Weight

Release date

Gemini 3 Pro

2025-11-18

Qwen3.6-27B

2026-04-21

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
Gemini 3 Pro has the higher public score estimate, 67.24 versus 52.73, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Gemini 3 Pro has the larger documented window (2M).

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

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Gemini 3 Pro
API / mo$10,500
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence45 rows

Agentic

  • Gemini 3 Pro63.23%
    Qwen3.6-27B54.84%

    Gemini 3 Pro leads this result

  • JobBench

    Gemini 3 Pro11.4%
    Source
    Qwen3.6-27B

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3 Pro
    Qwen3.6-27B59.3%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 3 Pro
    Qwen3.6-27B72.4%
    Source

    Not directly comparable

  • QwenClawBench

    Gemini 3 Pro
    Qwen3.6-27B53.4%
    Source

    Not directly comparable

  • QwenWebBench

    Gemini 3 Pro
    Qwen3.6-27B1487
    Source

    Not directly comparable

  • AndroidWorld

    Gemini 3 Pro
    Qwen3.6-27B70.3%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Gemini 3 Pro14.30%
    Source
    Qwen3.6-27B

    Not directly comparable

  • SWE-bench Verified

    Gemini 3 Pro
    Qwen3.6-27B77.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Gemini 3 Pro
    Qwen3.6-27B71.3%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemini 3 Pro
    Qwen3.6-27B53.5%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3 Pro
    Qwen3.6-27B59.3%
    Source

    Not directly comparable

  • LiveCodeBench

    Gemini 3 Pro
    Qwen3.6-27B83.9%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3 Pro
    Qwen3.6-27B36.2%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Gemini 3 Pro31.1%
    Source
    Qwen3.6-27B

    Not directly comparable

Knowledge

  • MMLU-Pro

    Gemini 3 Pro
    Qwen3.6-27B86.2%
    Source

    Not directly comparable

  • MMLU-Redux

    Gemini 3 Pro
    Qwen3.6-27B93.5%
    Source

    Not directly comparable

  • SuperGPQA

    Gemini 3 Pro
    Qwen3.6-27B66%
    Source

    Not directly comparable

  • C-Eval

    Gemini 3 Pro
    Qwen3.6-27B91.4%
    Source

    Not directly comparable

  • GPQA

    Gemini 3 Pro
    Qwen3.6-27B87.8%
    Source

    Not directly comparable

  • HLE

    Gemini 3 Pro
    Qwen3.6-27B24%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3 Pro37.600%
    Source
    Qwen3.6-27B

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3 Pro18.750%
    Source
    Qwen3.6-27B

    Not directly comparable

  • HMMT Feb 2025

    Gemini 3 Pro
    Qwen3.6-27B93.8%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Gemini 3 Pro
    Qwen3.6-27B90.7%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Gemini 3 Pro
    Qwen3.6-27B84.3%
    Source

    Not directly comparable

  • MMAnswerBench

    Gemini 3 Pro
    Qwen3.6-27B80.8%
    Source

    Not directly comparable

  • AIME26

    Gemini 3 Pro
    Qwen3.6-27B94.1%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemini 3 Pro81%
    Source
    Qwen3.6-27B75.8%
    Source

    Gemini 3 Pro leads this result

  • MathVision

    Gemini 3 Pro86.6%
    Source
    Qwen3.6-27B

    Not directly comparable

  • VideoMMMU

    Gemini 3 Pro87.6%
    Source
    Qwen3.6-27B84.4%
    Source

    Gemini 3 Pro leads this result

  • ScreenSpot Pro

    Gemini 3 Pro72.7%
    Source
    Qwen3.6-27B

    Not directly comparable

  • CharXiv

    Gemini 3 Pro81.4%
    Source
    Qwen3.6-27B78.4%
    Source

    Gemini 3 Pro leads this result

  • V*

    Gemini 3 Pro88.0%
    Source
    Qwen3.6-27B94.7%
    Source

    Qwen3.6-27B leads this result

  • MMMU

    Gemini 3 Pro
    Qwen3.6-27B82.9%
    Source

    Not directly comparable

  • RealWorldQA

    Gemini 3 Pro
    Qwen3.6-27B84.1%
    Source

    Not directly comparable

  • DynaMath

    Gemini 3 Pro
    Qwen3.6-27B85.6%
    Source

    Not directly comparable

  • MStar

    Gemini 3 Pro
    Qwen3.6-27B81.4%
    Source

    Not directly comparable

  • SimpleVQA

    Gemini 3 Pro
    Qwen3.6-27B56.1%
    Source

    Not directly comparable

  • CC-OCR

    Gemini 3 Pro
    Qwen3.6-27B81.2%
    Source

    Not directly comparable

  • CountBench

    Gemini 3 Pro
    Qwen3.6-27B97.8%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Gemini 3 Pro
    Qwen3.6-27B92.5%
    Source

    Not directly comparable

  • ERQA

    Gemini 3 Pro
    Qwen3.6-27B62.5%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 3 Pro
    Qwen3.6-27B87.7%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Gemini 3 Pro
    Qwen3.6-27B86.6%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3 Pro or Qwen3.6-27B?

Gemini 3 Pro has the higher public score estimate, 67.24 versus 52.73, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3 Pro or Qwen3.6-27B?

Gemini 3 Pro scores higher for coding on the public lane, 60.9 to 42.6. Gemini 3 Pro is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Gemini 3 Pro or Qwen3.6-27B?

Gemini 3 Pro scores higher for agentic tasks on the public lane, 59.6 to 33.9. Gemini 3 Pro is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Gemini 3 Pro or Qwen3.6-27B?

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, Gemini 3 Pro or Qwen3.6-27B?

Gemini 3 Pro has the larger documented context window: 2M, compared with 262K.

Related comparisons

Last updated September 4, 2026

Watch Gemini 3 Pro vs Qwen3.6-27B

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.