GPT-5.6 Cyber vs GPT-6 Astra vs Claude Mythos 5
Too close to call on our weighted score (GPT-6 Astra 36, Claude Mythos 5 36, GPT-5.6 Cyber 30). The right pick depends on what you value most.
OpenAIGPT-5.6 Cyber
30/100- ECI—
- Price$12.50 / $75.00
- Context400K
- OpenAI
GPT-6 Astra
36/100- ECI166.5
- Price$10.00 / $50.00
- Context1.05M
AnthropicClaude Mythos 5
36/100- ECI—
- Price$10.00 / $50.00
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (GPT-6 Astra 36/100, Claude Mythos 5 36/100, GPT-5.6 Cyber 30/100), so choose by what matters most for your work: GPT-6 Astra on price and GPT-6 Astra for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGPT-6 Astra and Claude Mythos 5GPT-6 Astra $20.00 · Claude Mythos 5 $20.00 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextGPT-6 AstraGPT-6 Astra 1,050,000 · Claude Mythos 5 1,000,000 · GPT-5.6 Cyber 400,000 tokens
- Widest inputsGPT-6 Astra and Claude Mythos 5GPT-5.6 Cyber: Text, Images · GPT-6 Astra: Text, Images, PDFs · Claude Mythos 5: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.6 Cyber | GPT-6 Astra | Claude Mythos 5 |
|---|---|---|---|---|
| Price | 50% | 0 | 0 | 0 |
| Inputs & features | 30% | 70 | 80 | 80 |
| Context window | 20% | 44 | 61 | 60 |
| Overall | 100% | 30/100 | 36/100 | 36/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.6 CyberOpenAI | GPT-6 AstraOpenAI | Claude Mythos 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 166.5 | — |
| ECI rank | — | #2 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 95.8% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 93.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% | — |
| SimpleQA VerifiedShort factual questions | — | 75.6% | — |
| Price per million tokens | |||
| Input | $12.50 | $10.00 (best) | $10.00 (best) |
| Output | $75.00 | $50.00 (best) | $50.00 (best) |
| Cached input | $1.25 | $1.00 (best) | — |
| Blended (3:1) | $28.13 | $20.00 (best) | $20.00 (best) |
| Long-context rate | Same rate | Over 272K: $20.00 / $75.00 | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Median of 2 providers |
| Limits | |||
| Context window | 400,000 tokens | 1,050,000 tokens (best) | 1,000,000 tokens |
| Max output | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-daybreak-red-latest | gpt-6-astra | — |
| API providers | 1 | 26 (best) | 2 |
| Released | Aug 7, 2026 | Sep 4, 2026 | Jun 9, 2026 |
| Knowledge cutoff | Feb 16, 2026 | Apr 30, 2026 | Jan 31, 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.6 Cyber$275.00
- GPT-6 Astra$200.00
- Claude Mythos 5$200.00
Which should you choose?
Which is better: GPT-5.6 Cyber, GPT-6 Astra or Claude Mythos 5?
It is close. Our weighted score puts them within a point (GPT-6 Astra 36/100, Claude Mythos 5 36/100, GPT-5.6 Cyber 30/100), so choose by what matters most for your work: GPT-6 Astra on price and GPT-6 Astra for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT-5.6 Cyber, GPT-6 Astra or Claude Mythos 5?
GPT-6 Astra is cheaper at $10.00 input / $50.00 output per million tokens (official OpenAI API price). Claude Mythos 5 costs $10.00 input / $50.00 output per million tokens (median across 2 API providers); GPT-5.6 Cyber costs $12.50 input / $75.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $20.00 per million tokens for GPT-6 Astra versus $20.00 for Claude Mythos 5 (1× as much) and $28.13 for GPT-5.6 Cyber (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.6 Cyber has not been scored yet, GPT-6 Astra has an ECI of 166.5 and Claude Mythos 5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Cyber, GPT-6 Astra and Claude Mythos 5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6 Astra has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Mythos 5 and 400,000 for GPT-5.6 Cyber. Maximum output per response: GPT-5.6 Cyber up to 128,000, GPT-6 Astra up to 128,000, Claude Mythos 5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Cyber accepts text and images; GPT-6 Astra accepts text, images and PDFs; Claude Mythos 5 accepts text, images and PDFs. GPT-6 Astra handles the widest range of inputs.
Are any of these open source?
No. GPT-5.6 Cyber, GPT-6 Astra and Claude Mythos 5 are proprietary and only available through APIs and apps.
Which is newer?
GPT-6 Astra is the newest, released Sep 4, 2026. GPT-5.6 Cyber came out Aug 7, 2026; Claude Mythos 5 came out Jun 9, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026, GPT-6 Astra Apr 30, 2026, Claude Mythos 5 Jan 31, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
