cohere--command-a-reasoning
sap-ai-core/command-a-reasoning出品方： sap-ai-core · 系列: command-a · 发布 2025-08-21 · 知识截止: 2024-06-01
⚠ 本模型为社区微调 / 衍生版本，非厂商官方发布。
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清单
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.
Coding59
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)8/20
- Provider availability1/10
Agents66
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output39
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume9/20
Cost efficiency44
- Headline price (log-scaled)44/95
- Has prompt-cache pricing0/5
Long context60
- Context window (100K → 2M)50/90
- 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 | $5.68 < $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 | $11.35 < $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 | $3.79 < $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 | $10.09 $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 | $10.59 $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
定价详情
推荐定价来自 sap-ai-core · cohere--command-a-reasoning
在 1 家渠道可用
| 服务商 | 服务商模型 ID | 输入 / 1M | 输出 / 1M | 上下文 | 发布日期 |
|---|---|---|---|---|---|
| SAP AI Core sap-ai-core | cohere--command-a-reasoning | $0.630 | $5.05 | 256K | 2025-08-21 |
Frequently asked questions
How much does cohere--command-a-reasoning cost?
cohere--command-a-reasoning costs $0.630 per 1M input tokens and $5.05 per 1M output tokens, sourced from sap-ai-core. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of cohere--command-a-reasoning?
cohere--command-a-reasoning has a context window of 256K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.
Does cohere--command-a-reasoning support tool calling?
Yes. cohere--command-a-reasoning 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 cohere--command-a-reasoning support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for cohere--command-a-reasoning in our data source. Verify with sap-ai-core's official documentation before relying on it in production.
Can cohere--command-a-reasoning accept image input?
No. cohere--command-a-reasoning only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is cohere--command-a-reasoning open-weight?
Yes. cohere--command-a-reasoning'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 cohere--command-a-reasoning?
If cohere--command-a-reasoning doesn't fit, consider text-embedding-3-large, amazon--titan-embed-text, sap-abap-1. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More sap-ai-core models
- text-embedding-3-large$0.09 in / $0.00 out
- amazon--titan-embed-text$0.14 in / $0.00 out
- sap-abap-1$0.48 in / $1.70 out
- amazon--nova-pro$0.56 in / $2.13 out
- amazon--nova-micro$0.03 in / $0.10 out
Capability lists this model is in
最近更新：
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.