claude-opus-5-5 vs gpt-6-astra
Parameters, independent leaderboard coverage, real-task reports and open-weight availability are shown side by side; missing coverage is not a zero.
Parameters
| Comparison item | claude-opus-5-5 | gpt-6-astra |
|---|---|---|
| Model Type | LLM | LLM |
| Context window | 1,000,000 tokens | 1,050,000 tokens |
| Maximum output | 128,000 tokens | 128,000 tokens |
| Input/output modalities | text, image → text | text, image → text |
| Endpoint | anthropic · openai | openai · openai-response |
| Open weights | Unavailable | Unavailable |
| License | Proprietary hosted model | Proprietary hosted model |
Leaderboard coverage
Every independent board covering either model is retained; an em dash means that board has not published a figure for that model.
A row marked as retrieved on different dates holds two readings taken on different days; a board re-fits or changes version as a whole between readings, so those two figures are not directly comparable.
| Evaluation | claude-opus-5-5 | gpt-6-astra |
|---|---|---|
| LMArena Text Arena — Arena score (Elo) | — | 1480 ±12 |
| LiveBench — Overall Retrieved on different dates | 83.2 (retrieved 2026-09-22) | 82.2 (retrieved 2026-09-12) |
| Artificial Analysis Intelligence Index — Intelligence Index Retrieved on different dates | 58 (retrieved 2026-09-22) | 53 (retrieved 2026-09-21) |
| Epoch Capabilities Index (ECI) — General ECI | — | 167 (163 - 172) |
| Vals Index — Accuracy (GDP-weighted finance, coding and legal) Retrieved on different dates | 66.16 ±1.00 (retrieved 2026-09-22) | 66.61 ±1.09 (retrieved 2026-09-21) |
| LMArena Text Arena · Coding — Arena score (Elo) | — | 1543 ±23 |
| LiveBench · Coding — Coding Retrieved on different dates | 89.3 (retrieved 2026-09-22) | 80.4 (retrieved 2026-09-12) |
| LiveBench · Agentic Coding — Agentic Coding Retrieved on different dates | 71.7 (retrieved 2026-09-22) | 57.3 (retrieved 2026-09-12) |
| Artificial Analysis · Output Speed — Median output tokens/s | — | 58 |
| Artificial Analysis · GDPval-AA v2.1 — Agentic Real-World Work Tasks, (Elo-500)/2000 (%) Retrieved on different dates | 67 (retrieved 2026-09-22) | 52 (retrieved 2026-09-21) |
| Artificial Analysis · Terminal-Bench v4.0 — Agentic Coding & Terminal Use (%) Retrieved on different dates | 60 (retrieved 2026-09-22) | 59 (retrieved 2026-09-21) |
| Artificial Analysis · MLCR-AA — Medical Long Context Reasoning (%) | — | 35.0 |
Real-task reports
claude-opus-5-5
- Claude Opus 5.5 and GPT-6 Sol on one interactive website prompt — Build an interactive website about imaginary planets from a single prompt. Finding: Opus 5.5 took 26 minutes and built a fuller, explorable solar system with more detail, using 16% of the $20 plan's usage; GPT-6 Sol took 10 minutes for three planets and 1% of the $200 plan's usage. Limitation: One prompt judged by the author; the usage shares are meters of two different subscription plans, not API costs.
- Four models build the Eiffel Tower in Three.js — Build the Eiffel Tower in Three.js. Finding: Opus 5.5 cost $8.95 and took 10 minutes; the author preferred its frontend and 3D detailing to GPT-6 Astra's ($7.45, 8 minutes), found GPT-6 Sol ($3.90, 5 minutes) disappointing and Kimi K3 ($4.04, 6 minutes) strong for the price. Limitation: One task judged by eye by the author; the post does not say how the models were run or how the costs were counted.
- Claude Pro, Codex Plus and SuperGrok on the same work at maximum settings — One piece of work run on each $20 subscription; the task itself is shown only in the author's video. Finding: Opus 5.5 used 10% of the weekly limit (115 million tokens) over 2 hours and scored 5/10, behind GPT-6 Sol at 7/10 (29 million tokens, 69 minutes) and Grok 4.7 at 6/10; the author still recommends Claude at $20 for its usage allowance. Limitation: The post does not describe the task, the quality score is the author's own, and the numbers are subscription meters rather than API usage.
- Eight weeks of Claude Code usage re-priced at Opus 5 and Opus 5.5 rates — Price every request from eight weeks of the author's own Claude Code transcripts at Opus 5 and Opus 5.5 list prices. Finding: 97% of the tokens were cache reads, so the same usage came to $2,849 at Opus 5.5 rates against $5,071 at Opus 5 rates — 44% less, rather than the 20% the headline input and output prices suggest. Limitation: It re-prices the same token counts and does not measure whether Opus 5.5 uses more or fewer tokens on the same work; list prices, not subscription billing; the author built the tool that read the transcripts.
gpt-6-astra
- Cortex AI: GPT-6 Astra, Gemini 3.8 Flash and Fable 5.1 on two real robot tasks — Load a sandwich into a microwave and close the door; attach a 5 mm tip to a pipette. Finding: GPT-6 Astra scored highest on both tasks, 80% on the microwave and 70% on the pipette, against 13.3% and 30% for Gemini 3.8 Flash and 6.7% and 20% for Fable 5.1; the lab credits it with retrying until the pipette tip docked and with checking that the microwave door latched. Limitation: The post does not say how many attempts each model had; scores are partial-credit judgements by the lab's evaluator, and the authors attribute the gap mainly to weaker depth perception in the lower-scoring models.
- GPT-6 Astra, Sol and Luna on one SVG animation prompt — Generate an SVG animation of a pelican riding a bicycle, shown in H5. Finding: GPT-6 Astra took 6 min 3 s and used 16% of the five-hour quota, against 4 min 42 s and 2% for GPT-6 Sol; the author recommends Sol when quota matters. Limitation: One prompt; the quota shares are a subscription meter, not API cost, and the post scores no output quality for Astra.
- Switching a coding project from GPT-6 Astra to DeepSeek V4.1 Flash — The author's own coding project, first on GPT-6 Astra and then on DeepSeek V4.1 Flash. Finding: About a dozen GPT-6 Astra turns cost the author $130 in a day without meeting the requirements; they switched the project back to DeepSeek V4.1 Flash. Limitation: One uncontrolled self-report; the post does not describe what the Astra turns were asked to do.
- Four models build the Eiffel Tower in Three.js — Build the Eiffel Tower in Three.js. Finding: GPT-6 Astra cost $7.45 and took 8 minutes; the author preferred Claude Opus 5.5's result ($8.95, 10 minutes) for this task. Limitation: One task judged by eye by the author; the post does not say how the models were run or how the costs were counted.