Kimi K3 vs GPT-5.3 Codex vs GPT-5.4
Too close to call on our weighted score (Kimi K3 65, GPT-5.4 65, GPT-5.3 Codex 64). The right pick depends on what you value most.
Moonshot AIKimi K3
65/100- ECI157.6
- Price$3.00 / $15.00
- Context1.05M
OpenAIGPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
- OpenAI
GPT-5.4
65/100- ECI156.9
- Price$2.50 / $15.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (Kimi K3 65/100, GPT-5.4 65/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: Kimi K3 for raw capability and GPT-5.3 Codex on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K3Capabilities Index (ECI): Kimi K3 157.6 · GPT-5.4 156.9 · GPT-5.3 Codex 156.8
- Lowest priceGPT-5.3 CodexGPT-5.3 Codex $4.81 · GPT-5.4 $5.63 · Kimi K3 $6.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.4 and Kimi K3GPT-5.4 1,050,000 · Kimi K3 1,048,576 · GPT-5.3 Codex 400,000 tokens
- Widest inputsSame inputsKimi K3: Text, Images, Video · GPT-5.3 Codex: Text, Images, PDFs · GPT-5.4: Text, Images, PDFs
- Self-hostingKimi K3Publishes downloadable weights
| Measure | Weight | Kimi K3 | GPT-5.3 Codex | GPT-5.4 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 88 | 87 | 87 |
| Price | 25% | 13 | 18 | 14 |
| Inputs & features | 15% | 80 | 80 | 80 |
| Context window | 10% | 61 | 44 | 61 |
| Overall | 100% | 65/100 | 64/100 | 65/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kimi K3Moonshot AI | GPT-5.3 CodexOpenAI | GPT-5.4OpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 157.6 (best) | 156.8 | 156.9 |
| ECI rank | #13 of 148 (best) | #18 of 148 | #16 of 148 |
| GPQA DiamondGraduate-level science questions | 93.1% | — | 93.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 72.2% | — | 78.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 97.2% | — | 97.8% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | 76.9% (best) |
| SimpleQA VerifiedShort factual questions | 50.6% (best) | — | 45.1% |
| Price per million tokens | |||
| Input | $3.00 | $1.75 (best) | $2.50 |
| Output | $15.00 | $14.00 (best) | $15.00 |
| Cached input | $0.30 | $0.175 (best) | $0.25 |
| Blended (3:1) | $6.00 | $4.81 (best) | $5.63 |
| Long-context rate | Same rate | Same rate | Over 272K: $5.00 / $22.50 |
| Price source | Official Moonshot AI API | Official OpenAI API | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens | 400,000 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 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 | Yes | No | No |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh | Yeslow · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | kimi-k3 | gpt-5.3-codex | gpt-5.4 |
| API providers | 68 (best) | 19 | 36 |
| Released | Jul 16, 2026 | Feb 5, 2026 | Mar 5, 2026 |
| Knowledge cutoff | — | Aug 31, 2025 | Aug 31, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Kimi K3$60.00
- GPT-5.3 Codex$45.50
- GPT-5.4$55.00
Which should you choose?
Which is better: Kimi K3, GPT-5.3 Codex or GPT-5.4?
It is close. Our weighted score puts them within a point (Kimi K3 65/100, GPT-5.4 65/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: Kimi K3 for raw capability and GPT-5.3 Codex on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Kimi K3, GPT-5.3 Codex or GPT-5.4?
GPT-5.3 Codex is cheaper at $1.75 input / $14.00 output per million tokens (official OpenAI API price). GPT-5.4 costs $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). At a typical mix of three input tokens to one output token, that is $4.81 per million tokens for GPT-5.3 Codex versus $5.63 for GPT-5.4 (1.2× as much) and $6.00 for Kimi K3 (1.2× as much).
Which scores higher on benchmarks?
Kimi K3 scores higher on the Capabilities Index (ECI): Kimi K3 157.6 (#13 of 148), GPT-5.4 156.9 (#16 of 148) and GPT-5.3 Codex 156.8 (#18 of 148). The confidence ranges of the top two overlap (154.9–160.4 vs 154.9–159.1), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K3 yet, so there is no like-for-like coding score. On overall capability, Kimi K3 leads, which tends to carry over to coding, but test on your own codebase. 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 400,000 for GPT-5.3 Codex. Maximum output per response: Kimi K3 up to 131,072, GPT-5.3 Codex up to 128,000, GPT-5.4 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K3 accepts text, images and video; GPT-5.3 Codex accepts text, images and PDFs; GPT-5.4 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-5.3 Codex and GPT-5.4 is proprietary.
Which is newer?
Kimi K3 is the newest, released Jul 16, 2026. GPT-5.4 came out Mar 5, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: GPT-5.3 Codex Aug 31, 2025, GPT-5.4 Aug 31, 2025.
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.
