Model profile
Alibaba

Qwen: Qwen3 VL 235B A22B Instruct

Qwen: Qwen3 VL 235B A22B Instruct is a budget-priced multimodal generalist from Alibaba with balanced runtime profile, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalBalanced latencyLarge contextBudget pricing
Intelligence
20.8

Benchmark blend

Coding
16.5

Dev workflow signal

Context
262K Tokens

Large

Input Price
$0.70

Budget tier

Decision snapshot
49

Qwen: Qwen3 VL 235B A22B Instruct currently reads as a budget multimodal option with large context and a balanced runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
Balanced
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
20.8
21

General reasoning and benchmark headroom.

Limited
Speed
59 tok/s
62

TTFT 1.04s

Competitive
Context
262K Tokens
88

How much prompt and task state can stay in view.

Above average
Price
$0.70
86

$2.80 output / 1M

Efficient

Editorial Profile

Qwen: Qwen3 VL 235B A22B Instruct in one narrative

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

Use-case specificCoding score 17Math score 71Vision enabled

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...

Identity

Alibaba multimodal profile

Positioning

Long-context research / Multimodal with large context and balanced 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 is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

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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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
20.8
MMLU Pro
82.3%
GPQA
71.2%
HLE
6.3%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
16.5
LiveCodeBench
0.594
SciCode
35.9%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
70.7
AIME 2025
70.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
42.7%
TAU2
35.1%
TerminalBench Hard
6.8%
LCR
31.7%

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
262K Tokens
Vision
Enabled
Modalities
image, text
Tokenizer
Qwen3
Moderation
No
Supported Parameters
frequency_penaltylogit_biasmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
Input Modalities
imagetext
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.70
Output
per 1M output tokens
$2.80
Blended
AA 3:1 mix
$1.23

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.