Qwen/Qwen2.5-72B-Instruct-128K
siliconflow-cn/qwen2-5-72b-instruct-128kPor siliconflow-cn · família: qwen · lançado 2024-09-18
⚠ Este é um fine-tune da comunidade ou derivado — não um lançamento oficial do fornecedor.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacidades
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding63
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability1/10
Agents61
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit0/15
- Provider availability1/10
JSON / structured output98
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume18/20
Cost efficiency61
- Headline price (log-scaled)61/95
- Has prompt-cache pricing0/5
Long context46
- Context window (100K → 2M)36/90
- Has published price for full window10/10
Production-readiness50
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $3.25 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $6.49 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $1.47 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $5.31 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $7.43 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Detalhes de preço
Preço recomendado de siliconflow-cn · Qwen/Qwen2.5-72B-Instruct-128K
Disponível em 1 provedores
| Provedor | ID do modelo do provedor | Entrada / 1M | Saída / 1M | Contexto | Lançado |
|---|---|---|---|---|---|
| SiliconFlow (China) siliconflow-cn | Qwen/Qwen2.5-72B-Instruct-128K | $0.590 | $0.590 | 131K | 2024-09-18 |
Frequently asked questions
How much does Qwen/Qwen2.5-72B-Instruct-128K cost?
Qwen/Qwen2.5-72B-Instruct-128K costs $0.590 per 1M input tokens and $0.590 per 1M output tokens, sourced from siliconflow-cn. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Qwen/Qwen2.5-72B-Instruct-128K?
Qwen/Qwen2.5-72B-Instruct-128K has a context window of 131K tokens, with a max output of 4K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen/Qwen2.5-72B-Instruct-128K support tool calling?
Yes. Qwen/Qwen2.5-72B-Instruct-128K supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Qwen/Qwen2.5-72B-Instruct-128K support structured output / JSON mode?
Yes. Qwen/Qwen2.5-72B-Instruct-128K supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Qwen/Qwen2.5-72B-Instruct-128K accept image input?
No. Qwen/Qwen2.5-72B-Instruct-128K only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen/Qwen2.5-72B-Instruct-128K open-weight?
No. Qwen/Qwen2.5-72B-Instruct-128K is a proprietary model — only siliconflow-cn (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Qwen/Qwen2.5-72B-Instruct-128K?
If Qwen/Qwen2.5-72B-Instruct-128K doesn't fit, consider inclusionAI/Ling-flash-2.0, inclusionAI/Ling-mini-2.0, inclusionAI/Ring-flash-2.0. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
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Capability lists this model is in
Última atualização:
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.