openai
OpenAI: GPT-6 Astra (batch)
openai/gpt-6-astra:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog describes openai/gpt-6-astra:batch as the batch variant of OpenAI's GPT-6 Astra, presented as a flagship for demanding end-to-end work such as analysis, software engineering, research, and document drafting. The listing reports text, image, and file inputs with text output, a context window of roughly one million tokens, and reasoning that is always enabled with selectable effort. Tool calling and structured outputs are also listed. No independent model card was available in this source pack, so capabilities remain vendor-described.[1]
Strengths
- According to the OpenRouter listing, inputs span text, images, and files with text output, paired with a context window of roughly one million tokens.[1]
- The catalog reports reasoning as always enabled, with effort selectable from low to max, which may suit tasks needing controllable deliberation.[1]
- Listed parameters include tool calling, tool choice, structured outputs, response format, seed, and verbosity, supporting integration into programmatic pipelines.[1]
Limitations
- Evidence comes only from the OpenRouter catalog; no independent model card was supplied, so vendor-described capabilities and any third-party index results should be validated on real workloads.[1]
- The catalog marks reasoning as mandatory, meaning it cannot be fully disabled through the listing's parameters.[1]
- The listing does not specify a knowledge cutoff and does not document how this batch variant behaves differently from the base model in practice.[1]
Where to use it
- Potentially suited to long-document analysis, deep research, and report drafting, matching the vendor-described positioning; confirm quality on representative inputs.[1]
- A candidate for software engineering and multi-step tool-using workflows, given the listed tool and structured-output support; pilot before adoption.[1]
- Worth evaluating for large-context tasks such as corpus review, where the listed context window could reduce chunking, subject to workload testing.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-6 Astra (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...
Specifications
- Model ID
- openai/gpt-6-astra:batch
- Canonical ID
- openai/gpt-6-astra-20260903
- Creator
- openai
- Added to OpenRouter
- 04.09.2026
- Context length
- 1,050,000
- Modality
- text+image+file->text
- Input modalities
- file, image, text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $5 / out $25
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | SS — top 10% of the cohort | reasoning: mandatory · default medium · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | SS — top 10% of the cohort | — |
| Agents | SS — top 10% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 56.9 | SS — top 10% of the cohort | 13.11.2026 |
| Artificial Analysis | Coding index | 76.9 | SS — top 10% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 51 | SS — top 10% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| OpenAI | 1,050,000 | $5 | $25 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.