Grok 4.3 vs Kimi K2.7 Code vs Qwen3.8 27B
Too close to call on our weighted score (Qwen3.8 27B 67, Grok 4.3 67, Kimi K2.7 Code 64). The right pick depends on what you value most.
xAIGrok 4.3
67/100- ECI149.2
- Price$1.25 / $2.50
- Context1M
Moonshot AIKimi K2.7 Code
64/100- ECI150.0
- Price$0.95 / $4.00
- Context262K
Alibaba (Qwen)Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3.8 27B 67/100, Grok 4.3 67/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability, Qwen3.8 27B on price and Grok 4.3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2.7 CodeCapabilities Index (ECI): Kimi K2.7 Code 150.0 · Qwen3.8 27B 149.4 · Grok 4.3 149.2
- Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · Grok 4.3 $1.56 · Kimi K2.7 Code $1.71 per 1M tokens (3:1 blend)
- Longest contextGrok 4.3Grok 4.3 1,000,000 · Kimi K2.7 Code 262,144 · Qwen3.8 27B 262,144 tokens
- Widest inputsSame inputsGrok 4.3: Text, Images, PDFs · Kimi K2.7 Code: Text, Images, Video · Qwen3.8 27B: Text, Images, Video
- Self-hostingKimi K2.7 Code and Qwen3.8 27BPublishes downloadable weights
| Measure | Weight | Grok 4.3 | Kimi K2.7 Code | Qwen3.8 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 77 | 78 | 77 |
| Price | 25% | 41 | 39 | 51 |
| Inputs & features | 15% | 80 | 80 | 80 |
| Context window | 10% | 60 | 37 | 37 |
| Overall | 100% | 67/100 | 64/100 | 67/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Grok 4.3xAI | Kimi K2.7 CodeMoonshot AI | Qwen3.8 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.2 | 150.0 (best) | 149.4 |
| ECI rank | #55 of 148 | #49 of 148 (best) | #53 of 148 |
| GPQA DiamondGraduate-level science questions | 88.8% (best) | 87.9% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 42.8% | 54.0% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% | 95.6% (best) | — |
| SimpleQA VerifiedShort factual questions | 33.2% | 36.5% (best) | — |
| Price per million tokens | |||
| Input | $1.25 | $0.95 | $0.40 (best) |
| Output | $2.50 (best) | $4.00 | $2.50 (best) |
| Cached input | $0.20 | $0.19 (best) | — |
| Blended (3:1) | $1.56 | $1.71 | $0.925 (best) |
| Long-context rate | Over 200K: $2.50 / $5.00 | Same rate | Same rate |
| Price source | Official xAI API | Official Moonshot AI API | Median of 39 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 30,000 tokens | 262,144 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · medium · high | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | grok-4.3 | kimi-k2.7-code | — |
| API providers | 27 | 51 (best) | 41 |
| Released | Apr 17, 2026 | Jun 12, 2026 | Aug 14, 2026 |
| Knowledge cutoff | — | Jan 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Grok 4.3$17.50
- Kimi K2.7 Code$17.50
- Qwen3.8 27B$9.00
Which should you choose?
Which is better: Grok 4.3, Kimi K2.7 Code or Qwen3.8 27B?
It is close. Our weighted score puts them within a point (Qwen3.8 27B 67/100, Grok 4.3 67/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability, Qwen3.8 27B 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, Grok 4.3, Kimi K2.7 Code or Qwen3.8 27B?
Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Grok 4.3 costs $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). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $1.56 for Grok 4.3 (1.7× as much) and $1.71 for Kimi K2.7 Code (1.9× as much).
Which scores higher on benchmarks?
Kimi K2.7 Code scores higher on the Capabilities Index (ECI): Kimi K2.7 Code 150.0 (#49 of 148), Qwen3.8 27B 149.4 (#53 of 148) and Grok 4.3 149.2 (#55 of 148). The confidence ranges of the top two overlap (148.1–151.8 vs 147.5–151.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.3, Kimi K2.7 Code and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Kimi K2.7 Code 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 262,144 for Kimi K2.7 Code and 262,144 for Qwen3.8 27B. Maximum output per response: Grok 4.3 up to 30,000, Kimi K2.7 Code up to 262,144, Qwen3.8 27B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Grok 4.3 accepts text, images and PDFs; Kimi K2.7 Code accepts text, images and video; Qwen3.8 27B accepts text, images and video. They handle the same number of input types.
Are any of these open source?
Kimi K2.7 Code and Qwen3.8 27B publishes its weights and can be self-hosted; Grok 4.3 is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Kimi K2.7 Code came out Jun 12, 2026; Grok 4.3 came out Apr 17, 2026. Knowledge cutoff: Kimi K2.7 Code Jan 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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