Kimi K2.7 Code vs GPT-5.3 Codex vs Grok 4.3
Too close to call on our weighted score (Grok 4.3 67, Kimi K2.7 Code 64, GPT-5.3 Codex 64). The right pick depends on what you value most.
Moonshot AIKimi K2.7 Code
64/100- ECI150.0
- Price$0.95 / $4.00
- Context262K
OpenAIGPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
xAIGrok 4.3
67/100- ECI149.2
- Price$1.25 / $2.50
- Context1M
Too close to call
It is close. Our weighted score puts them within 2 points (Grok 4.3 67/100, Kimi K2.7 Code 64/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: GPT-5.3 Codex for raw capability, Grok 4.3 on price and Grok 4.3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.3 CodexCapabilities Index (ECI): GPT-5.3 Codex 156.8 · Kimi K2.7 Code 150.0 · Grok 4.3 149.2
- Lowest priceGrok 4.3Grok 4.3 $1.56 · Kimi K2.7 Code $1.71 · GPT-5.3 Codex $4.81 per 1M tokens (3:1 blend)
- Longest contextGrok 4.3Grok 4.3 1,000,000 · GPT-5.3 Codex 400,000 · Kimi K2.7 Code 262,144 tokens
- Widest inputsSame inputsKimi K2.7 Code: Text, Images, Video · GPT-5.3 Codex: Text, Images, PDFs · Grok 4.3: Text, Images, PDFs
- Self-hostingKimi K2.7 CodePublishes downloadable weights
| Measure | Weight | Kimi K2.7 Code | GPT-5.3 Codex | Grok 4.3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 87 | 77 |
| Price | 25% | 39 | 18 | 41 |
| Inputs & features | 15% | 80 | 80 | 80 |
| Context window | 10% | 37 | 44 | 60 |
| Overall | 100% | 64/100 | 64/100 | 67/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kimi K2.7 CodeMoonshot AI | GPT-5.3 CodexOpenAI | Grok 4.3xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.0 | 156.8 (best) | 149.2 |
| ECI rank | #49 of 148 | #18 of 148 (best) | #55 of 148 |
| GPQA DiamondGraduate-level science questions | 87.9% | — | 88.8% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 54.0% (best) | — | 42.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 95.6% (best) | — | 93.3% |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | — |
| SimpleQA VerifiedShort factual questions | 36.5% (best) | — | 33.2% |
| Price per million tokens | |||
| Input | $0.95 (best) | $1.75 | $1.25 |
| Output | $4.00 | $14.00 | $2.50 (best) |
| Cached input | $0.19 | $0.175 (best) | $0.20 |
| Blended (3:1) | $1.71 | $4.81 | $1.56 (best) |
| Long-context rate | Same rate | Same rate | Over 200K: $2.50 / $5.00 |
| Price source | Official Moonshot AI API | Official OpenAI API | Official xAI API |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens | 1,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 128,000 tokens | 30,000 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 | Yes | Yeslow · medium · high · xhigh | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | kimi-k2.7-code | gpt-5.3-codex | grok-4.3 |
| API providers | 51 (best) | 19 | 27 |
| Released | Jun 12, 2026 | Feb 5, 2026 | Apr 17, 2026 |
| Knowledge cutoff | Jan 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 K2.7 Code$17.50
- GPT-5.3 Codex$45.50
- Grok 4.3$17.50
Which should you choose?
Which is better: Kimi K2.7 Code, GPT-5.3 Codex or Grok 4.3?
It is close. Our weighted score puts them within 2 points (Grok 4.3 67/100, Kimi K2.7 Code 64/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: GPT-5.3 Codex for raw capability, Grok 4.3 on price and Grok 4.3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Kimi K2.7 Code, GPT-5.3 Codex or Grok 4.3?
Grok 4.3 is cheaper at $1.25 input / $2.50 output per million tokens (official xAI API price). Kimi K2.7 Code costs $0.95 input / $4.00 output per million tokens (official Moonshot AI API price); GPT-5.3 Codex costs $1.75 input / $14.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.56 per million tokens for Grok 4.3 versus $1.71 for Kimi K2.7 Code (1.1× as much) and $4.81 for GPT-5.3 Codex (3.1× as much).
Which scores higher on benchmarks?
GPT-5.3 Codex scores higher on the Capabilities Index (ECI): GPT-5.3 Codex 156.8 (#18 of 148), Kimi K2.7 Code 150.0 (#49 of 148) and Grok 4.3 149.2 (#55 of 148). Their confidence ranges do not overlap (153.5–160.8 vs 148.1–151.8), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2.7 Code and Grok 4.3 yet, so there is no like-for-like coding score. On overall capability, GPT-5.3 Codex 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?
Grok 4.3 has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.3 Codex and 262,144 for Kimi K2.7 Code. Maximum output per response: Kimi K2.7 Code up to 262,144, GPT-5.3 Codex up to 128,000, Grok 4.3 up to 30,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K2.7 Code accepts text, images and video; GPT-5.3 Codex accepts text, images and PDFs; Grok 4.3 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
Kimi K2.7 Code publishes its weights and can be self-hosted; GPT-5.3 Codex and Grok 4.3 is proprietary.
Which is newer?
Kimi K2.7 Code is the newest, released Jun 12, 2026. Grok 4.3 came out Apr 17, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: Kimi K2.7 Code Jan 2025, GPT-5.3 Codex 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.
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