GPT-6 Astra

openai/gpt-6-astra-20260903

OpenAI's GPT-6 Astra is a multimodal model that accepts file, image, and text inputs and generates text outputs. It features a 1,050,000-token context window, supports tool use and reasoning, and is a proprietary model released in September 2026.

  • tool use
  • structured outputs
  • reasoning

At a glance

provideropenai
releasedSep 3, 2026
context1.1M
input / M$10

Specifications

What the API gives you

Context window
1.1M tokens
Max output
128K tokens
Input price
$10 / 1M tokens
Output price
$50 / 1M tokens
Cache read
$1 / 1M tokens
Modalities
file, image, text → text
Knowledge cutoff
—
Released
Sep 3, 2026

Measured evidence

Public benchmark record

FACTS Grounding
82%2026-09-11evaluated 2026-09-11
FrontierMath Tiers 1-3 (Epoch AI)‡
93.7% ± 1.42026-08-30max effort, evaluated 2026-08-30
GPQA Diamond (Epoch AI)‡
95.8% ± 1.42026-08-30max effort, evaluated 2026-08-30
LiveBench Coding
80.4%2026-10-18
LiveBench Language
89.4%2026-10-18
LiveBench Math
96.8%2026-10-18
LiveBench Reasoning
92.7%2026-10-18
LMArena Agent‡
15.12026-10-19max effort
LMArena Agent Bash Recovery‡
5.52026-10-08max effort
LMArena Agent Steerability‡
15.52026-10-19max effort
LMArena Agent Task Outcome‡
12.82026-10-19max effort
LMArena Agent Tool Hallucination‡
0.72026-10-19max effort
LMArena Creative Writing
1421 Elo2026-10-15
LMArena Long Query
1461 Elo2026-10-15
LMArena Math
1465 Elo2026-10-15
LMArena Search Factuality
1240 Elo2026-10-13
LMArena Text
1477 Elo2026-10-15
LMArena Text Factuality
1466 Elo2026-10-15
LMArena Vision‡
1285 Elo2026-10-19max effort
LMArena Vision Diagrams‡
1310 Elo2026-10-19max effort
LMArena Vision OCR‡
1299 Elo2026-10-19max effort
LMArena WebDev‡
1774 Elo2026-10-19max effort
LMArena WebDev Image-to-Web‡
1726 Elo2026-10-19max effort
OTIS Mock AIME (Epoch AI)‡
100% ± 02026-08-30max effort, evaluated 2026-08-30
SimpleQA Verified (Epoch AI)‡
75.6% ± 1.42026-08-30max effort, evaluated 2026-08-30
Terminal-Bench (4.0)‡
58.2%2026-10-20Codex, max effort, evaluated 2026-09-03

LMArena data licensed CC-BY-4.0. Aider (Apache-2.0) and SWE-bench (MIT) are open. Design Arena uses blind human preference. ‡ Submitted scaffold plus model result. Compare the harness and effort settings, not only the model name.

Task evidence

How broad is the support?

Each status is exact to this model version and the selected task. Official release claims remain provisional.

  • Best LLM for Competition MathEstablished evidence

    100% of intended weighted task evidence across 4 independent sources. 6 of 6 configured evaluation feeds currently have results.

  • Best LLM for Business WritingEstablished evidence

    100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • 100% of intended weighted task evidence across 3 independent sources. 5 of 5 configured evaluation feeds currently have results.

  • Best LLM for Marketing CopyEstablished evidence

    100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Chat & RoleplayEstablished evidence

    100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Creative WritingEstablished evidence

    100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

Show all 45 tasks
  • Best LLM for WritingEstablished evidence

    100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • 100% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Math & ReasoningEstablished evidence

    100% of intended weighted task evidence across 5 independent sources. 7 of 7 configured evaluation feeds currently have results.

  • 100% of intended weighted task evidence across 3 independent sources. 6 of 6 configured evaluation feeds currently have results.

  • 85% of intended weighted task evidence across 3 independent sources. 5 of 6 configured evaluation feeds currently have results.

  • Best LLM for SummarizationEstablished evidence

    85% of intended weighted task evidence across 3 independent sources. 5 of 6 configured evaluation feeds currently have results.

  • Best LLM for Grounded RAGEstablished evidence

    81% of intended weighted task evidence across 3 independent sources. 5 of 7 configured evaluation feeds currently have results.

  • Best LLM for Code CompletionEstablished evidence

    79% of intended weighted task evidence across 2 independent sources. 3 of 3 configured evaluation feeds currently have results.

  • 72% of intended weighted task evidence across 2 independent sources. 5 of 6 configured evaluation feeds currently have results.

  • Best LLM for Autonomous AgentsEstablished evidence

    67% of intended weighted task evidence across 3 independent sources. 6 of 6 configured evaluation feeds currently have results.

  • 64% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • 61% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • Best LLM for Agentic CodingEstablished evidence

    60% of intended weighted task evidence across 3 independent sources. 7 of 7 configured evaluation feeds currently have results.

  • Best LLM for Fast SummariesEstablished evidence

    58% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • Best Value LLMEstablished evidence

    58% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • Best LLM for AI AgentsEstablished evidence

    50% of intended weighted task evidence across 3 independent sources. 9 of 9 configured evaluation feeds currently have results.

  • 50% of intended weighted task evidence across 2 independent sources. 3 of 4 configured evaluation feeds currently have results.

  • 50% of intended weighted task evidence across 2 independent sources. 3 of 4 configured evaluation feeds currently have results.

  • Best LLM for TranslationEstablished evidence

    50% of intended weighted task evidence across 2 independent sources. 3 of 4 configured evaluation feeds currently have results.

  • Best LLM for CodingEstablished evidence

    49% of intended weighted task evidence across 3 independent sources. 7 of 7 configured evaluation feeds currently have results.

  • Best LLM for Hermes AgentEstablished evidence

    48% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for OpenHandsEstablished evidence

    48% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for GooseEstablished evidence

    48% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for OpenClawEstablished evidence

    48% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best Local LLM for CodingEstablished evidence

    47% of intended weighted task evidence across 2 independent sources. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Frontend & UIEstablished evidence

    45% of intended weighted task evidence across 2 independent sources. 6 of 6 configured evaluation feeds currently have results.

  • Best Cheap LLM for High VolumeEstablished evidence

    40% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • Cheapest Capable LLMEstablished evidence

    40% of intended weighted task evidence across 2 independent sources. 2 of 3 configured evaluation feeds currently have results.

  • 35% of intended weighted task evidence across 2 independent sources. 3 of 4 configured evaluation feeds currently have results.

  • 35% of intended weighted task evidence across 2 independent sources. 3 of 4 configured evaluation feeds currently have results.

  • 33% of intended weighted task evidence across 2 independent sources. 5 of 5 configured evaluation feeds currently have results.

  • Best LLM for OCR & DocumentsProvisional evidence

    65% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Structured-output eval or VLMEvalKit tasks. 3 of 5 configured evaluation feeds currently have results.

  • Best LLM for Charts & DiagramsProvisional evidence

    65% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Structured-output eval or VLMEvalKit tasks. 3 of 5 configured evaluation feeds currently have results. Official release evidence is also tracked provisionally.

  • 60% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Structured-output eval or VLMEvalKit tasks. 4 of 6 configured evaluation feeds currently have results.

  • Best LLM for Document ParsingProvisional evidence

    58% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Structured-output eval or VLMEvalKit tasks. 3 of 5 configured evaluation feeds currently have results.

  • Best LLM for Massive ContextProvisional evidence

    47% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from LongBench v2. 2 of 3 configured evaluation feeds currently have results.

  • 46% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Berkeley Function Calling or Structured-output eval. 6 of 7 configured evaluation feeds currently have results.

  • 21% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Route reliability or Structured-output eval. 1 of 3 configured evaluation feeds currently have results.

  • 17% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Berkeley Function Calling or OSWorld Verified. 3 of 3 configured evaluation feeds currently have results. Official release evidence is also tracked provisionally.

Official release evidence · provisional

What the launch material actually says

Verbatim claims from the model provider. These help on launch day but do not count as independent confirmation.

Recommendation coverage

Where this model appears

  1. #2Best LLM for Computer & Browser Use
  2. #2Best LLM for Grounded RAG
  3. #2Best LLM for Tool & Function Calling
  4. #4Best LLM for Everyday Translation
  5. #4Best LLM for Autonomous Agents
  6. #4Best LLM for OpenHands
  7. #4Best LLM for Debugging & Code Review
  8. #4Best LLM for Logic & Problem Solving
  9. #4Best LLM for AI Agents
  10. #4Best LLM for Literary Translation
  11. #4Best LLM for OpenClaw
  12. #4Best LLM for Hermes Agent
  13. #4Best LLM for RAG & Long Context
  14. #4Best LLM for Translation
  15. #4Best LLM for Goose
  16. #5Best LLM for Competition Math
  17. #5Best LLM for Agentic Coding
  18. #6Best LLM for Math & Reasoning
  19. #7Best LLM for Frontend & UI
  20. #7Best LLM for JSON & Schema Output
  21. #7Best LLM for a General Assistant
  22. #7Best LLM for Structured Data Extraction
  23. #8Best LLM for Coding
  24. #8Best LLM for Image Understanding
  25. #8Best LLM for Creative Writing
  26. #8Best LLM for Writing

Compare head to head

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