Model profile
Alibaba
New in 2026

Qwen: Qwen3.6 Plus

Qwen: Qwen3.6 Plus is a budget-priced multimodal generalist from Alibaba with partial runtime data, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalN/A latencyLarge contextBudget pricing
Intelligence
40.5

Benchmark blend

Coding
54.5

Dev workflow signal

Context
1000K Tokens

Large

Input Price
$0.50

Budget tier

Decision snapshot
64

Qwen: Qwen3.6 Plus currently reads as a budget multimodal option with large context and a partially published runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Multimodal
Latency tier
N/A
Price tier
Budget
Source coverage
OpenRouterArtificial AnalysisVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
40.5
41

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
1000K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$0.50
86

$3.00 output / 1M

Efficient

Editorial Profile

Qwen: Qwen3.6 Plus in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 55Math score N/AVision enabled

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...

Identity

Alibaba multimodal profile

Positioning

Long-context research / Multimodal with large context and partially published runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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Context
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Intelligence
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Context
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Input Price
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
40.5
GPQA
88.2%
HLE
27.8%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
54.5
SciCode
40.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
75.2%
TAU2
97.7%
TerminalBench Hard
43.9%
LCR
72.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1000K Tokens
Vision
Enabled
Modalities
image, text, video
Tokenizer
Qwen3
Max Completion
65536
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogprobsmax_tokenspresence_penaltyreasoningresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Input Modalities
imagetextvideo
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.50
Output
per 1M output tokens
$3.00
Blended
AA 3:1 mix
$1.13

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

OR Cache Write
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.