Qwen2.5-Omni 7B
alibaba/qwen2-5-omni-7b出品方： Alibaba (Qwen) · 系列: qwen · 發布 2024-12 · 知識截止: 2024-04
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清單
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.
Coding42
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability2/10
Agents37
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit0/15
- Provider availability2/10
JSON / structured output49
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency70
- Headline price (log-scaled)70/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Vision70
- Accepts image input50/50
- Context window (10K → 1M)8/30
- Has published price10/10
- Provider availability2/10
Production-readiness70
- Number of independent providers10/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
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 | $0.70 < $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 | $1.40 < $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 | $0.40 < $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 | $1.20 < $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 | $1.44 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
定價詳情
推薦定價來自 alibaba · qwen2-5-omni-7b
最便宜的渠道： alibaba-cn · $0.087 輸入 + $0.345 輸出
於 2 家供應商可用
| 服務商 | 服務商模型 ID | 輸入 / 1M | 輸出 / 1M | 上下文 | 發布日期 |
|---|---|---|---|---|---|
| Alibaba alibaba | qwen2-5-omni-7b | $0.100 | $0.400 | 33K | 2024-12 |
| Alibaba (China) alibaba-cn | qwen2-5-omni-7b | $0.087 | $0.345 | 33K | 2024-12 |
Frequently asked questions
How much does Qwen2.5-Omni 7B cost?
Qwen2.5-Omni 7B costs $0.100 per 1M input tokens and $0.400 per 1M output tokens, sourced from alibaba. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Qwen2.5-Omni 7B?
Qwen2.5-Omni 7B has a context window of 33K tokens, with a max output of 2K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen2.5-Omni 7B support tool calling?
Yes. Qwen2.5-Omni 7B 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 Qwen2.5-Omni 7B support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen2.5-Omni 7B in our data source. Verify with Alibaba (Qwen)'s official documentation before relying on it in production.
Can Qwen2.5-Omni 7B accept image input?
Yes. Qwen2.5-Omni 7B accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Alibaba (Qwen)'s docs for the exact rule.
Is Qwen2.5-Omni 7B open-weight?
Yes. Qwen2.5-Omni 7B's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Qwen2.5-Omni 7B?
If Qwen2.5-Omni 7B doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3 235B A22B Instruct 2507. 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.
Explore more
More Alibaba (Qwen) models
- Qwen3.5 397B-A17B$0.60 in / $3.60 out
- Qwen3 32B$0.70 in / $2.80 out
- Qwen3 235B A22B Instruct 2507$0.10 in / $0.10 out
- Qwen3-Coder 480B-A35B Instruct$1.50 in / $7.50 out
- Qwen3-235B-A22B-Thinking-2507$0.10 in / $0.10 out
Capability lists this model is in
最近更新：
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.