Model profile
Alibaba
New in 2026

Qwen: Qwen3.8 27B

Qwen: Qwen3.8 27B is a budget-priced multimodal generalist from Alibaba with partial runtime data, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsN/A latencyLarge contextBudget pricing
Intelligence
52.0

Benchmark blend

Coding
68.1

Dev workflow signal

Context
1000K Tokens

Large

Input Price
$0.45

Budget tier

Decision snapshot
71

Qwen: Qwen3.8 27B currently reads as a budget multimodal option with large context and a partially published runtime profile.

Overall profile
Strong all-rounder
Best for
Long-context research / Agent workflows
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
52.0
52

General reasoning and benchmark headroom.

Situational
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
$0.45
86

$3.20 output / 1M

Efficient

Editorial Profile

Qwen: Qwen3.8 27B in one narrative

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

Strong all-rounderCoding score 68Math score N/AVision enabled

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...

Identity

Alibaba multimodal profile

Positioning

Long-context research / Agent workflows 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
  • Coding indicators point to a strong developer workflow fit.

  • 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
  • Code generation, refactors, test writing, and tool-assisted debugging.

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

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

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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
52.0
GPQA
90.5%
HLE
33.9%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
68.1
SciCode
44.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
77.3%

Extra benchmark cuts are not available for this category yet.

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
Qwen
Max Completion
131072
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokenspresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Input Modalities
imagetextvideo
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.45
Output
per 1M output tokens
$3.20
Blended
AA 3:1 mix
$1.14

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

OR Cache Read
$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.