Alibaba Cloud · multimodal · Released 2025-05-02

Qwen3 Instruct: pricing, context window and benchmarks

Qwen3 Instruct is a multimodal model from Alibaba Cloud. It offers a 1,000,000-token context window, costs $5.06 per million input tokens and $25.39 per million output tokens, and averages 79.8 across the index's benchmark suite.

codingvisionlong contextopen weightsmultimodal
Input price
$5.06
per 1M tokens
Output price
$25.39
per 1M tokens
Context
1,000,000
tokens
Avg score
79.8
rank #127 of 600
Arena Elo
1419.2
modelled
Max output
128,000
tokens

Pricing

Qwen3 Instruct costs $5.06 per million input tokens and $25.39 per million output tokens. A blended 3:1 input-to-output mix works out to about $10.14 per million tokens. Cached input is listed at $0.57 per million tokens.

ItemPriceNotes
Input$5.06per 1M tokens
Output$25.39per 1M tokens
Cached input$0.57per 1M tokens
Blended 3:1$10.14estimate per 1M tokens
1M in + 1M out$30.45estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.3 177 71th
GPQA Diamond 74.1 166 72th
SWE-bench Verified 68.5 134 78th
HumanEval 85.1 112 81th
MATH-500 86.1 91 85th
AIME 2025 78.5 108 82th
LiveCodeBench 71.1 171 72th
IFEval 89.1 79 87th
TruthfulQA 79.7 196 67th
HellaSwag 87.0 179 70th
MMMU 78.7 80 87th
Arena Elo 1419.2 153 75th

What Qwen3 Instruct is good for

Qwen3 Instruct is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.06 per million input tokens, it sits in the mid-range of the index, and the 1,000,000-token context window is enough for large files and multi-file diffs.

Strengths

  • Large 1,000,000-token context window for long documents and agent traces.
  • Open weights make self-hosting, fine-tuning and data-residency review possible.
  • Accepts more than text, including image input where the provider supports it.
  • Coding benchmarks are a relative strength within its tier.

Trade-offs

  • No standout weakness in the indexed specifications, but real-world behaviour still needs testing.

How it compares

ModelProviderContextInput / 1MAvg score
Command A Turbo Cohere 32768 $13.53 79.8
ERNIE 4.5 Reasoning Baidu 1000000 $14.36 79.8
GLM-4.6 Chat Zhipu AI 400000 $4.89 79.8
Magistral Mistral AI 200000 $4.75 79.8
Qwen3 Instruct Alibaba Cloud 1000000 $5.06 79.8
Doubao 1.5 Pro ByteDance 200000 $13.65 79.7

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FAQ

How much does Qwen3 Instruct cost?

Qwen3 Instruct is listed at $5.06 per million input tokens and $25.39 per million output tokens. Cached input is $0.57 per million tokens. A blended 3:1 input-to-output mix is about $10.14 per million tokens.

What is the context window of Qwen3 Instruct?

Qwen3 Instruct has a context window of 1,000,000 tokens and can emit up to 128,000 output tokens per request in this index.

Is Qwen3 Instruct open weights?

Yes. Qwen3 Instruct is listed as an open-weight model under a open weights licence.

How does Qwen3 Instruct score on benchmarks?

Qwen3 Instruct averages 79.8 across the scored benchmarks in this index, ranking #127 of 600 models. Its strongest relative result is Arena Elo at 1419.2.

What is Qwen3 Instruct best for?

Qwen3 Instruct is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.06 per million input tokens, it sits in the mid-range of the index, and the 1,000,000-token context window is enough for large files and multi-file diffs.

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