GPT-5.6 Cyber vs Claude Mythos 5 vs Claude Opus 4.8
Too close to call on our weighted score (Claude Opus 4.8 37, 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
AnthropicClaude Mythos 5
36/100- ECI—
- Price$10.00 / $50.00
- Context1M
- Anthropic
Claude Opus 4.8
37/100- ECI158.3
- Price$5.00 / $25.00
- Context1M
Too close to call
It is close. Our weighted score puts them within 1 points (Claude Opus 4.8 37/100, Claude Mythos 5 36/100, GPT-5.6 Cyber 30/100), so choose by what matters most for your work: Claude Opus 4.8 on price. 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 priceClaude Opus 4.8Claude Opus 4.8 $10.00 · Claude Mythos 5 $20.00 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextClaude Mythos 5 and Claude Opus 4.8Claude Mythos 5 1,000,000 · Claude Opus 4.8 1,000,000 · GPT-5.6 Cyber 400,000 tokens
- Widest inputsClaude Mythos 5 and Claude Opus 4.8GPT-5.6 Cyber: Text, Images · Claude Mythos 5: Text, Images, PDFs · Claude Opus 4.8: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5.6 Cyber | Claude Mythos 5 | Claude Opus 4.8 |
|---|---|---|---|---|
| Price | 50% | 0 | 0 | 2 |
| Inputs & features | 30% | 70 | 80 | 80 |
| Context window | 20% | 44 | 60 | 60 |
| Overall | 100% | 30/100 | 36/100 | 37/100 |
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 | Claude Mythos 5Anthropic | Claude Opus 4.8Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 158.3 |
| ECI rank | — | — | #12 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 91.0% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 80.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 98.3% |
| SimpleQA VerifiedShort factual questions | — | — | 53.0% |
| Price per million tokens | |||
| Input | $12.50 | $10.00 | $5.00 (best) |
| Output | $75.00 | $50.00 | $25.00 (best) |
| Cached input | $1.25 | — | $0.50 (best) |
| Blended (3:1) | $28.13 | $20.00 | $10.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 2 providers | Official Anthropic API |
| Limits | |||
| Context window | 400,000 tokens | 1,000,000 tokens (best) | 1,000,000 tokens (best) |
| 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 | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-daybreak-red-latest | — | claude-opus-4-8 |
| API providers | 1 | 2 | 45 (best) |
| Released | Aug 7, 2026 | Jun 9, 2026 | May 28, 2026 |
| Knowledge cutoff | Feb 16, 2026 | Jan 31, 2026 | Jan 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
- Claude Mythos 5$200.00
- Claude Opus 4.8$100.00
Which should you choose?
Which is better: GPT-5.6 Cyber, Claude Mythos 5 or Claude Opus 4.8?
It is close. Our weighted score puts them within 1 points (Claude Opus 4.8 37/100, Claude Mythos 5 36/100, GPT-5.6 Cyber 30/100), so choose by what matters most for your work: Claude Opus 4.8 on price. 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, Claude Mythos 5 or Claude Opus 4.8?
Claude Opus 4.8 is cheaper at $5.00 input / $25.00 output per million tokens (official Anthropic 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 $10.00 per million tokens for Claude Opus 4.8 versus $20.00 for Claude Mythos 5 (2× as much) and $28.13 for GPT-5.6 Cyber (2.8× 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, Claude Mythos 5 has not been scored yet and Claude Opus 4.8 has an ECI of 158.3.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Cyber, Claude Mythos 5 and Claude Opus 4.8 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?
Claude Mythos 5 and Claude Opus 4.8 have the largest context windows (1,000,000 and 1,000,000 tokens), against 400,000 for GPT-5.6 Cyber. Maximum output per response: GPT-5.6 Cyber up to 128,000, Claude Mythos 5 up to 128,000, Claude Opus 4.8 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Cyber accepts text and images; Claude Mythos 5 accepts text, images and PDFs; Claude Opus 4.8 accepts text, images and PDFs. Claude Mythos 5 handles the widest range of inputs.
Are any of these open source?
No. GPT-5.6 Cyber, Claude Mythos 5 and Claude Opus 4.8 are proprietary and only available through APIs and apps.
Which is newer?
GPT-5.6 Cyber is the newest, released Aug 7, 2026. Claude Mythos 5 came out Jun 9, 2026; Claude Opus 4.8 came out May 28, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026, Claude Mythos 5 Jan 31, 2026, Claude Opus 4.8 Jan 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.
