Kimi K2.7 Code vs Muse Spark 1.2 vs Grok 4.3
Muse Spark 1.2 comes out ahead, 72 to 67 and 64 on our weighted score, though Grok 4.3 is 22% cheaper per token.
Moonshot AIKimi K2.7 Code
64/100- ECI150.0
- Price$0.95 / $4.00
- Context262K
- Our pick
MetaMuse Spark 1.2
72/100- ECI155.0
- Price$1.25 / $4.25
- Context1.05M
xAIGrok 4.3
67/100- ECI149.2
- Price$1.25 / $2.50
- Context1M
Muse Spark 1.2 is our pick
Muse Spark 1.2 is the better all-round choice, scoring 72/100 against Grok 4.3 (67) and Kimi K2.7 Code (64). It leads on capability and inputs & features. Grok 4.3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMuse Spark 1.2Capabilities Index (ECI): Muse Spark 1.2 155.0 · 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 · Muse Spark 1.2 $2.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.2Muse Spark 1.2 1,048,576 · Grok 4.3 1,000,000 · Kimi K2.7 Code 262,144 tokens
- Widest inputsMuse Spark 1.2Kimi K2.7 Code: Text, Images, Video · Muse Spark 1.2: Text, Images, PDFs, Audio, Video · Grok 4.3: Text, Images, PDFs
- Self-hostingKimi K2.7 CodePublishes downloadable weights
| Measure | Weight | Kimi K2.7 Code | Muse Spark 1.2 | Grok 4.3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 84 | 77 |
| Price | 25% | 39 | 36 | 41 |
| Inputs & features | 15% | 80 | 100 | 80 |
| Context window | 10% | 37 | 61 | 60 |
| Overall | 100% | 64/100 | 72/100 | 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 | Muse Spark 1.2Meta | Grok 4.3xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.0 | 155.0 (best) | 149.2 |
| ECI rank | #49 of 148 | #30 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% |
| SimpleQA VerifiedShort factual questions | 36.5% | 60.3% (best) | 33.2% |
| Price per million tokens | |||
| Input | $0.95 (best) | $1.25 | $1.25 |
| Output | $4.00 | $4.25 | $2.50 (best) |
| Cached input | $0.19 | $0.15 (best) | $0.20 |
| Blended (3:1) | $1.71 | $2.00 | $1.56 (best) |
| Long-context rate | Same rate | Same rate | Over 200K: $2.50 / $5.00 |
| Price source | Official Moonshot AI API | Official Meta API | Official xAI API |
| Limits | |||
| Context window | 262,144 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 262,144 tokens (best) | 131,072 tokens | 30,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | Yes | No |
| Video | Yes | Yes | No |
| Reasoning | Yes | Yesminimal · low · 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 | muse-spark-1.2 | grok-4.3 |
| API providers | 51 (best) | 15 | 27 |
| Released | Jun 12, 2026 | Aug 5, 2026 | Apr 17, 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.
- Kimi K2.7 Code$17.50
- Muse Spark 1.2$21.00
- Grok 4.3$17.50
Which should you choose?
Which is better: Kimi K2.7 Code, Muse Spark 1.2 or Grok 4.3?
Muse Spark 1.2 is the better all-round choice, scoring 72/100 against Grok 4.3 (67) and Kimi K2.7 Code (64). It leads on capability and inputs & features. Grok 4.3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Kimi K2.7 Code, Muse Spark 1.2 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); Muse Spark 1.2 costs $1.25 input / $4.25 output per million tokens (official Meta 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 $2.00 for Muse Spark 1.2 (1.3× as much).
Which scores higher on benchmarks?
Muse Spark 1.2 scores higher on the Capabilities Index (ECI): Muse Spark 1.2 155.0 (#30 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 (152.8–157.5 vs 148.1–151.8), so the gap is a real one. On individual benchmarks: SimpleQA Verified — Muse Spark 1.2 60.3%, Kimi K2.7 Code 36.5%, Grok 4.3 33.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2.7 Code, Muse Spark 1.2 and Grok 4.3 yet, so there is no like-for-like coding score. On overall capability, Muse Spark 1.2 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?
Muse Spark 1.2 has the largest context window at 1,048,576 tokens, against 1,000,000 for Grok 4.3 and 262,144 for Kimi K2.7 Code. Maximum output per response: Kimi K2.7 Code up to 262,144, Muse Spark 1.2 up to 131,072, 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; Muse Spark 1.2 accepts text, images, PDFs, audio and video; Grok 4.3 accepts text, images and PDFs. Muse Spark 1.2 handles the widest range of inputs.
Are any of these open source?
Kimi K2.7 Code publishes its weights and can be self-hosted; Muse Spark 1.2 and Grok 4.3 is proprietary.
Which is newer?
Muse Spark 1.2 is the newest, released Aug 5, 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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