Qwen: Qwen2.5 VL 72B Instruct API Pricing
Qwen: Qwen2.5 VL 72B Instruct costs $0.800 per 1M input tokens and $1.00 per 1M output tokens (cache reads: $0.400). Context window: 128K. Prices verified 2026-10-21 · source
Alternatives to consider
Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.
High adoption means battle-tested weights, more fine-tunes/quants, and faster bug fixes. View on HuggingFace →
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Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $0.800 | — |
| Cache read | $0.400 | −50% |
| Output | $1.00 | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Training data ends here — newer events require retrieval or web search.
What would Qwen: Qwen2.5 VL 72B Instruct cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $10.40 |
| Coding agent | 5,000 | 8,000 / 2,000 | $42.00 |
| RAG pipeline | 30,000 | 4,000 / 500 | $111.00 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $34.00 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Qwen: Qwen2.5 VL 72B Instruct
Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.
Compare Qwen: Qwen2.5 VL 72B Instruct with
- 72B Instruct vs OpenAI: GPT-5.6 Terra Pro
- 72B Instruct vs Anthropic: Claude Fable 5
- 72B Instruct vs Anthropic: Claude Opus 5
- 72B Instruct vs OpenAI: GPT-5.6 Sol
Popular head-to-heads — see all on the comparisons index.
Frequently asked questions
How much does Qwen: Qwen2.5 VL 72B Instruct cost?
Qwen: Qwen2.5 VL 72B Instruct costs $0.800 per 1M input tokens and $1.00 per 1M output tokens; cached input tokens cost $0.400 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
128K tokens, with up to 115K output tokens per response. That's roughly 160 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.400/1M, about 50% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 97% on a typical workload with comparable quality.
Official resources
- Qwen: Qwen2.5 VL 72B Instruct on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- Qwen GitHub → — official model repositories and release notes.
- Shred your current bill — paste a CSV and see if switching saves money.