DiffusionGemma 26B A4B IT vs GPT-5.6 Cyber vs Claude Mythos 5
Claude Mythos 5 comes out ahead, 72 to 60 and 51 on our weighted score, and it is the cheaper option too.
GoogleDiffusionGemma 26B A4B IT
51/100- ECI—
- Price—
- Context262K
OpenAIGPT-5.6 Cyber
60/100- ECI—
- Price$12.50 / $75.00
- Context400K
- Our pick
AnthropicClaude Mythos 5
72/100- ECI—
- Price$10.00 / $50.00
- Context1M
Claude Mythos 5 is our pick
Claude Mythos 5 is the better all-round choice, scoring 72/100 against GPT-5.6 Cyber (60) and DiffusionGemma 26B A4B IT (51). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 Mythos 5Claude Mythos 5 $20.00 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend) · DiffusionGemma 26B A4B IT unpriced
- Longest contextClaude Mythos 5Claude Mythos 5 1,000,000 · GPT-5.6 Cyber 400,000 · DiffusionGemma 26B A4B IT 262,144 tokens
- Widest inputsClaude Mythos 5DiffusionGemma 26B A4B IT: Text, Images · GPT-5.6 Cyber: Text, Images · Claude Mythos 5: Text, Images, PDFs
- Self-hostingDiffusionGemma 26B A4B ITPublishes downloadable weights (Apache 2.0)
| Measure | Weight | DiffusionGemma 26B A4B IT | GPT-5.6 Cyber | Claude Mythos 5 |
|---|---|---|---|---|
| Inputs & features | 60% | 60 | 70 | 80 |
| Context window | 40% | 37 | 44 | 60 |
| Overall | 100% | 51/100 | 60/100 | 72/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DiffusionGemma 26B A4B ITGoogle | GPT-5.6 CyberOpenAI | Claude Mythos 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $12.50 | $10.00 (best) |
| Output | — | $75.00 | $50.00 (best) |
| Cached input | — | $1.25 | — |
| Blended (3:1) | — | $28.13 | $20.00 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official OpenAI API | Median of 2 providers |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Proprietary |
| API model ID | — | gpt-daybreak-red-latest | — |
| API providers | 1 | 1 | 2 (best) |
| Released | Jun 9, 2026 | Aug 7, 2026 | Jun 9, 2026 |
| Knowledge cutoff | Jan 2025 | Feb 16, 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.
- DiffusionGemma 26B A4B IT—
- GPT-5.6 Cyber$275.00
- Claude Mythos 5$200.00
Which should you choose?
Which is better: DiffusionGemma 26B A4B IT, GPT-5.6 Cyber or Claude Mythos 5?
Claude Mythos 5 is the better all-round choice, scoring 72/100 against GPT-5.6 Cyber (60) and DiffusionGemma 26B A4B IT (51). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DiffusionGemma 26B A4B IT, GPT-5.6 Cyber or Claude Mythos 5?
Claude Mythos 5 is cheaper at $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 Claude Mythos 5 versus $28.13 for GPT-5.6 Cyber (1.4× as much). DiffusionGemma 26B A4B IT has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DiffusionGemma 26B A4B IT has not been scored yet, GPT-5.6 Cyber has not been scored yet and Claude Mythos 5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DiffusionGemma 26B A4B IT, 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?
Claude Mythos 5 has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.6 Cyber and 262,144 for DiffusionGemma 26B A4B IT. Maximum output per response: DiffusionGemma 26B A4B IT up to 32,768, GPT-5.6 Cyber up to 128,000, Claude Mythos 5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
DiffusionGemma 26B A4B IT accepts text and images; GPT-5.6 Cyber accepts text and images; Claude Mythos 5 accepts text, images and PDFs. Claude Mythos 5 handles the widest range of inputs.
Are any of these open source?
DiffusionGemma 26B A4B IT publishes its weights (Apache 2.0) and can be self-hosted; GPT-5.6 Cyber and Claude Mythos 5 is proprietary.
Which is newer?
GPT-5.6 Cyber is the newest, released Aug 7, 2026. DiffusionGemma 26B A4B IT came out Jun 9, 2026; Claude Mythos 5 came out Jun 9, 2026. Knowledge cutoff: DiffusionGemma 26B A4B IT Jan 2025, GPT-5.6 Cyber Feb 16, 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.
