GPT-5.4 vs Kimi K3 vs Claude Mythos 5
Too close to call on our weighted score (GPT-5.4 43, Kimi K3 43, Claude Mythos 5 36). The right pick depends on what you value most.
OpenAIGPT-5.4
43/100- ECI156.9
- Price$2.50 / $15.00
- Context1.05M
Moonshot AIKimi K3
43/100- ECI157.6
- Price$3.00 / $15.00
- 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-5.4 43/100, Kimi K3 43/100, Claude Mythos 5 36/100), so choose by what matters most for your work: GPT-5.4 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 · Kimi K3 $6.00 · Claude Mythos 5 $20.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.4 and Kimi K3GPT-5.4 1,050,000 · Kimi K3 1,048,576 · Claude Mythos 5 1,000,000 tokens
- Widest inputsSame inputsGPT-5.4: Text, Images, PDFs · Kimi K3: Text, Images, Video · Claude Mythos 5: Text, Images, PDFs
- Self-hostingKimi K3Publishes downloadable weights
| Measure | Weight | GPT-5.4 | Kimi K3 | Claude Mythos 5 |
|---|---|---|---|---|
| Price | 50% | 14 | 13 | 0 |
| Inputs & features | 30% | 80 | 80 | 80 |
| Context window | 20% | 61 | 61 | 60 |
| Overall | 100% | 43/100 | 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-5.4OpenAI | Kimi K3Moonshot AI | Claude Mythos 5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.9 | 157.6 (best) | — |
| ECI rank | #16 of 148 | #13 of 148 (best) | — |
| GPQA DiamondGraduate-level science questions | 93.3% (best) | 93.1% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 78.6% (best) | 72.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 97.8% (best) | 97.2% | — |
| SWE-bench VerifiedFixing real GitHub issues | 76.9% | — | — |
| SimpleQA VerifiedShort factual questions | 45.1% | 50.6% (best) | — |
| Price per million tokens | |||
| Input | $2.50 (best) | $3.00 | $10.00 |
| Output | $15.00 (best) | $15.00 (best) | $50.00 |
| Cached input | $0.25 (best) | $0.30 | — |
| Blended (3:1) | $5.63 (best) | $6.00 | $20.00 |
| Long-context rate | Over 272K: $5.00 / $22.50 | Same rate | Same rate |
| Price source | Official OpenAI API | Official Moonshot AI API | Median of 2 providers |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 1,048,576 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high · xhigh | Yeslow · high · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-5.4 | kimi-k3 | — |
| API providers | 36 | 68 (best) | 2 |
| Released | Mar 5, 2026 | Jul 16, 2026 | Jun 9, 2026 |
| Knowledge cutoff | 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-5.4$55.00
- Kimi K3$60.00
- Claude Mythos 5$200.00
Which should you choose?
Which is better: GPT-5.4, Kimi K3 or Claude Mythos 5?
It is close. Our weighted score puts them within a point (GPT-5.4 43/100, Kimi K3 43/100, Claude Mythos 5 36/100), so choose by what matters most for your work: GPT-5.4 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-5.4, Kimi K3 or Claude Mythos 5?
GPT-5.4 is cheaper at $2.50 input / $15.00 output per million tokens (official OpenAI API price). Kimi K3 costs $3.00 input / $15.00 output per million tokens (official Moonshot AI API price); Claude Mythos 5 costs $10.00 input / $50.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $5.63 per million tokens for GPT-5.4 versus $6.00 for Kimi K3 (1.1× as much) and $20.00 for Claude Mythos 5 (3.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.4 has an ECI of 156.9, Kimi K3 has an ECI of 157.6 and Claude Mythos 5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K3 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 and Kimi K3 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Claude Mythos 5. Maximum output per response: GPT-5.4 up to 128,000, Kimi K3 up to 131,072, Claude Mythos 5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.4 accepts text, images and PDFs; Kimi K3 accepts text, images and video; Claude Mythos 5 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
Kimi K3 publishes its weights and can be self-hosted; GPT-5.4 and Claude Mythos 5 is proprietary.
Which is newer?
Kimi K3 is the newest, released Jul 16, 2026. Claude Mythos 5 came out Jun 9, 2026; GPT-5.4 came out Mar 5, 2026. Knowledge cutoff: 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.
