GPT-5.6 Cyber vs GPT-5.4 vs Claude Mythos 5
GPT-5.4 comes out ahead, 43 to 36 and 30 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.6 Cyber
30/100- ECI—
- Price$12.50 / $75.00
- Context400K
- Our pickOpenAI
GPT-5.4
43/100- ECI156.9
- Price$2.50 / $15.00
- Context1.05M
AnthropicClaude Mythos 5
36/100- ECI—
- Price$10.00 / $50.00
- Context1M
GPT-5.4 is our pick
GPT-5.4 is the better all-round choice, scoring 43/100 against Claude Mythos 5 (36) and GPT-5.6 Cyber (30). It leads 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 priceGPT-5.4GPT-5.4 $5.63 · Claude Mythos 5 $20.00 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextGPT-5.4GPT-5.4 1,050,000 · Claude Mythos 5 1,000,000 · GPT-5.6 Cyber 400,000 tokens
- Widest inputsGPT-5.4 and Claude Mythos 5GPT-5.6 Cyber: Text, Images · GPT-5.4: 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-5.4 | Claude Mythos 5 |
|---|---|---|---|---|
| Price | 50% | 0 | 14 | 0 |
| Inputs & features | 30% | 70 | 80 | 80 |
| Context window | 20% | 44 | 61 | 60 |
| Overall | 100% | 30/100 | 43/100 | 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-5.4OpenAI | Claude Mythos 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 156.9 | — |
| ECI rank | — | #16 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 93.3% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 78.6% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 97.8% | — |
| SWE-bench VerifiedFixing real GitHub issues | — | 76.9% | — |
| SimpleQA VerifiedShort factual questions | — | 45.1% | — |
| Price per million tokens | |||
| Input | $12.50 | $2.50 (best) | $10.00 |
| Output | $75.00 | $15.00 (best) | $50.00 |
| Cached input | $1.25 | $0.25 (best) | — |
| Blended (3:1) | $28.13 | $5.63 (best) | $20.00 |
| Long-context rate | Same rate | Over 272K: $5.00 / $22.50 | 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 | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gpt-daybreak-red-latest | gpt-5.4 | — |
| API providers | 1 | 36 (best) | 2 |
| Released | Aug 7, 2026 | Mar 5, 2026 | Jun 9, 2026 |
| Knowledge cutoff | Feb 16, 2026 | Aug 31, 2025 | 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-5.4$55.00
- Claude Mythos 5$200.00
Which should you choose?
Which is better: GPT-5.6 Cyber, GPT-5.4 or Claude Mythos 5?
GPT-5.4 is the better all-round choice, scoring 43/100 against Claude Mythos 5 (36) and GPT-5.6 Cyber (30). It leads 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, GPT-5.4 or Claude Mythos 5?
GPT-5.4 is cheaper at $2.50 input / $15.00 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 $5.63 per million tokens for GPT-5.4 versus $20.00 for Claude Mythos 5 (3.6× as much) and $28.13 for GPT-5.6 Cyber (5× 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-5.4 has an ECI of 156.9 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 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-5.4 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-5.4 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-5.4 accepts text, images and PDFs; Claude Mythos 5 accepts text, images and PDFs. GPT-5.4 handles the widest range of inputs.
Are any of these open source?
No. GPT-5.6 Cyber, GPT-5.4 and Claude Mythos 5 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; GPT-5.4 came out Mar 5, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026, GPT-5.4 Aug 31, 2025, 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.
