Intelligence
10 scoreAlibaba · Flagships Analysis
Qwen2.5 Max
Intelligence, Performance & Price Analysis
Canonical slug: qwen-2-5-max · Canonical model registry at build time
Input Price
$1.60 / 1M tokensOutput Price
$6.40 / 1M tokensExecutive Assessment
Routing Verdict & Tradeoffs
Ethen Routing Verdict
Capable everyday model
Qwen2.5 Max scores 10 (estimated) on the Artificial Analysis Intelligence Index, placing it below average among other non-reasoning models in a similar price tier (median: 17). Qwen2.5 Max costs $1.60 per 1M input tokens (better than average, median: $1.88) and $6.40 per 1M output tokens (better than average, median: $7.75), based on Alibaba's API.
Good for routine tasks; route complex reasoning and premium workloads to stronger models.
Task Fit Assessment
| Workload | Rating | Notes |
|---|---|---|
| Complex reasoning & agentic workflows | viable | Intelligence score 10 handles routine reasoning but may struggle with open-ended agentic tasks. |
| Cost-sensitive pipelines | viable | Output pricing at $6.40 is premium. Route high-volume simple tasks to cheaper alternatives. |
Cost Pressure Analysis
High
Pricing is premium — input $1.60, output $6.40. This model is expensive for high-volume or output-heavy workloads.
Technical Specifications
Architecture and Limits
| Specification | Value | Validation Authority |
|---|---|---|
| Model type | Proprietary | inferred |
| Reasoning | No | faq |
| Input modalities | Qwen2.5 Max supports text input. | faq |
| Output modalities | Qwen2.5 Max supports text output. | faq |
| Context window | 32k tokens | faq |
| Open weights / source | No, Qwen2.5 Max is proprietary. The model weights are not publicly available. | faq |
| Parameters | Qwen2.5 Max is a proprietary model and Alibaba has not disclosed the model size or parameter count. | faq |
| API availability | Yes, Qwen2.5 Max is available via API through 1 provider. | faq |
Evidence charts
Profile visualizations
Charts are the same canonical evidence cards previously published for this slug, contained inside the D18D page grammar.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Larger context windows enable complex multi-turn tasks but may increase latency and cost for long inputs.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Retrieved 2026-07-08
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Methodology
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Qwen2.5 Max.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Frequently Asked Questions
Model FAQs & Technical Disclosures
Qwen2.5 Max was released on January 28, 2025.
Qwen2.5 Max was created by Alibaba.
Qwen2.5 Max scores 10 (estimated) on the Artificial Analysis Intelligence Index, placing it below average among other non-reasoning models in a similar price tier (median: 17).
Qwen2.5 Max costs $1.60 per 1M input tokens (better than average, median: $1.88) and $6.40 per 1M output tokens (better than average, median: $7.75), based on Alibaba's API.
Qwen2.5 Max costs $1.60 per 1M input tokens and $6.40 per 1M output tokens (based on Alibaba's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $2.08 per 1M tokens. Pricing may vary by provider.
No, Qwen2.5 Max is not a reasoning model. It provides direct responses without extended chain-of-thought reasoning.
Qwen2.5 Max supports text input.
Qwen2.5 Max supports text output.
No, Qwen2.5 Max does not support image input. It can only process text.
No, Qwen2.5 Max is not multimodal. It only supports text input.
Qwen2.5 Max has a context window of 32k tokens. This determines how much text and conversation history the model can process in a single request.
No, Qwen2.5 Max is proprietary. The model weights are not publicly available.
Qwen2.5 Max is a proprietary model and Alibaba has not disclosed the model size or parameter count.
Qwen2.5 Max achieves a score of 10 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Qwen2.5 Max is available via API through 1 provider.
Qwen2.5 Max is available through 1 API provider.