qwen3.5
Input price$0.1
Output price$0.15
AlibabaTextVision
qwen3.8-max
qwen3.8-max is Alibaba's model at $2.00 input and $6.00 output per million tokens, with a 1000K context window. On a typical 3:1 input-to-output mix that blends to roughly $3.00 per million tokens, placing it in the premium band of the 68 models tracked here — cheaper than 27% of them.
Context window1000K
Input price$2 / 1M
Output price$6 / 1M
Output speed70 tok/s
Quality score94
Data updatedUpdated Aug 2026
Price verified2026-08-06 · Official
Price noteFlat rate across the full context, no long-prompt surcharge; implicit cache reads $0.25 / 1M
By price, qwen3.8-max ranks 46th cheapest of 68 on input and 45th on output. Its quality score of 94 ranks 9th of 68, and on value (quality score ÷ output price) it ranks 44th of 68. Its blended rate sits 9% above the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $350 per month on qwen3.8-max, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $416. Because output is priced 3.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 1000K context window holds roughly 1,333 pages of A4 text (at ~750 tokens per page), ranking 22nd of 68 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis. Output runs at about 70 tok/s (50th fastest of 68), acceptable interactively, though long responses will feel slow.
We track 6 Alibaba models, and qwen3.8-max's blended rate sits 296% above that provider's average. If your task tolerates a little less headroom, qwen3.5 (Alibaba) blends about 96% cheaper at a quality score of 91, and is worth benchmarking first. Going the other way, gpt-5.6-terra scores 95 on quality for about 25% less.
The closest model in Alibaba's line-up is qwen3.5-plus ($0.40 input / $2.40 output, quality 89). Against it, qwen3.8-max scores 5 points higher on quality, runs 30 tok/s slower (about 30%), costs 70% more blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $350 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $416 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $360 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $2,080 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| qwen3.8-max | Alibaba | $3.00 | 94 | — |
| qwen3.5Cheaper option | Alibaba | $0.11 | 91 | -96% |
| gpt-5.6-terraHigher quality | OpenAI | $2.25 | 95 | -25% |
| qwen3.5-plusSame provider | Alibaba | $0.90 | 89 | -70% |
Best for
ReasoningCodingLong Context
Modalities
TextVision
Where it fits — and where it doesn't
Good fit
- Coding: writing, refactoring and debugging across multi-file project context.
- Reasoning: multi-step decomposition, planning and tasks that need rigorous inference.
- Long documents: a 1000K window ingests a full contract, paper or large codebase in one pass.
- Multimodal input: handles images, screenshots and scanned documents directly.
Poor fit
- High-frequency batch jobs: at $3.00 blended per million tokens, bills scale quickly at volume.
Frequently asked questions
How much does the qwen3.8-max API cost?
qwen3.8-max costs $2.00 per million input tokens and $6.00 per million output tokens. On a 3:1 input-to-output mix that blends to about $3.00 per million tokens.
What does qwen3.8-max cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $350/month, RAG document Q&A about $416/month, a coding assistant about $360/month, and batch summarization about $2,080/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the qwen3.8-max context window?
1000K tokens — roughly 1,333 pages of A4 text at ~750 tokens per page, ranking 22nd of the 68 models tracked here.
qwen3.8-max or qwen3.5 — which is better value?
qwen3.5 blends to about $0.11 per million tokens versus $3.00 for qwen3.8-max — roughly 96% cheaper — at a quality score of 91 against 94. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with qwen3.8-max. Benchmark both on your own data before deciding.
What is qwen3.8-max best suited for?
Tagged use cases: reasoning, coding, long-context. Coding: writing, refactoring and debugging across multi-file project context. Less suitable: High-frequency batch jobs: at $3.00 blended per million tokens, bills scale quickly at volume.
How current is this qwen3.8-max pricing?
Pricing here was last verified on 2026-08-06 against official documentation. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against Alibaba's official pricing page before you commit.
Estimate the real cost of this model
Bring tokens per request and monthly volume into the calculator to compare total model costs.
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Pricing, speed and quality scores change over time. Confirm official documentation before production use.