GPT 6 Astra
gpt-6-astraCompare gpt-6-astra API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 1.1M
- Maximum input window
- Max output
- 128K
- Maximum tokens per response
- Modalities
- →
- Knowledge cutoff
- Apr 2026
- Released
- Sep 2026
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
o200k_basePerformance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·GPT 6 Astra
Intelligence Index
GPT 6 astra
52.7
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About GPT 6 Astra
适合真正复杂的问题
GPT-6 Astra 是面向高难度工作的推理模型。它适合问题尚未完全定义、材料存在冲突、需要比较多种方案的场景，例如梳理复杂系统设计、评估研究结论、审查一组相互依赖的代码改动，或把大量资料整理成有论据的专业文档。
从分析到成果制作
模型支持文本和图片输入，可以结合说明文档、界面截图、图表与代码进行分析。对于长材料，任务重点不只是摘要，而是找出材料之间的关系：哪项结论有证据支持，哪些约束互相冲突，哪个假设会改变最终建议。给出交付对象和验收条件，有助于它把分析转成可直接审阅的报告、方案或代码。
工具让推理接触实际结果
通过 Responses API 配合已启用的工具，它可以参与检索、代码执行、文件处理和计算机操作等多步骤流程。应用应把工具结果交回模型，让后续判断依据实际输出更新；只生成执行计划还不等于任务完成。需要复杂研究时，也应让模型区分材料中的事实、推断与尚未解决的问题。
Astra 适合优先追求结果质量的任务。使用时可以要求它比较方案、说明取舍、检查反例，再给出最终建议。对于长流程，分阶段设定可检查的成果，比一次要求包办全部工作更容易把握方向，也便于在关键处补充新信息。
Use cases and prompting
研究评估示例
“下面是三份关于同一产品方案的研究材料，结论存在冲突。请按目标用户、实验方法和证据强度比较它们，指出差异能否由样本或假设解释。然后提出一份两周内可执行的验证计划，列出每项实验的判断标准，以及哪些结果会推翻当前建议。”
提供原始材料、预算和截止时间，让建议能够落地。
怎样避免只有长分析，没有明确决策？
指定交付结构：推荐方案、关键证据、取舍、执行步骤和待确认项。允许模型在证据不足时保留结论，而不是要求它强行选择。
能直接完成研究里的计算和检索吗？
需要应用通过 Responses API 提供相应工具。评估完成度时，应检查实际工具结果和最终产物。
API access
API documentation
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| OpenAI | Unlimited | Unlimited | Unlimited |
| Azure | Unlimited | Unlimited | Unlimited |
| default | Unlimited | Unlimited | Unlimited |
| GPT官+AZ 混合 | Unlimited | Unlimited | Unlimited |
| GPT特价 | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about gpt-6-astra
What is gpt-6-astra?
Compare gpt-6-astra API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call gpt-6-astra?
Create an API key with access to gpt-6-astra, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is gpt-6-astra priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of gpt-6-astra?
The model catalog lists a context window of 1050000 tokens. Check the selected endpoint for request limits.
What is the maximum output of gpt-6-astra?
The model catalog lists a maximum output of 128000 tokens. Your request settings may set a lower limit.
How should I evaluate gpt-6-astra for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.