Kimi K2.6 vs DeepSeek-V3.1 vs Grok 4.20 (Reasoning)
Grok 4.20 (Reasoning) comes out ahead, 68 to 65 and 55 on our weighted score, though DeepSeek-V3.1 is 2.6× cheaper per token.
Moonshot AIKimi K2.6
65/100- ECI151.1
- Price$0.95 / $4.00
- Context262K
DeepSeekDeepSeek-V3.1
55/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
- Our pick
xAIGrok 4.20 (Reasoning)
68/100- ECI152.0
- Price$1.25 / $2.50
- Context1M
Grok 4.20 (Reasoning) is our pick
Grok 4.20 (Reasoning) is the better all-round choice, scoring 68/100 against Kimi K2.6 (65) and DeepSeek-V3.1 (55). It leads on context window. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGrok 4.20 (Reasoning)Capabilities Index (ECI): Grok 4.20 (Reasoning) 152.0 · Kimi K2.6 151.1 · DeepSeek-V3.1 139.9
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Grok 4.20 (Reasoning) $1.56 · Kimi K2.6 $1.71 per 1M tokens (3:1 blend)
- Longest contextGrok 4.20 (Reasoning)Grok 4.20 (Reasoning) 1,000,000 · Kimi K2.6 262,144 · DeepSeek-V3.1 131,072 tokens
- Widest inputsKimi K2.6 and Grok 4.20 (Reasoning)Kimi K2.6: Text, Images, Video · DeepSeek-V3.1: Text · Grok 4.20 (Reasoning): Text, Images, PDFs
- Self-hostingKimi K2.6 and DeepSeek-V3.1Publishes downloadable weights (MIT License)
| Measure | Weight | Kimi K2.6 | DeepSeek-V3.1 | Grok 4.20 (Reasoning) |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 79 | 65 | 81 |
| Price | 25% | 39 | 60 | 41 |
| Inputs & features | 15% | 80 | 35 | 80 |
| Context window | 10% | 37 | 24 | 60 |
| Overall | 100% | 65/100 | 55/100 | 68/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Kimi K2.6Moonshot AI | DeepSeek-V3.1DeepSeek | Grok 4.20 (Reasoning)xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.1 | 139.9 | 152.0 (best) |
| ECI rank | #45 of 148 | #100 of 148 | #41 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 90.8% (best) | — | 89.3% |
| FrontierMath Tiers 1–3Research-level mathematics | 57.2% (best) | — | 44.9% |
| OTIS Mock AIME 2024–2025Competition mathematics | 96.1% (best) | — | 92.2% |
| SWE-bench VerifiedFixing real GitHub issues | 76.7% | — | — |
| SimpleQA VerifiedShort factual questions | 34.9% (best) | — | 30.2% |
| Price per million tokens | |||
| Input | $0.95 | $0.385 (best) | $1.25 |
| Output | $4.00 | $1.25 (best) | $2.50 |
| Cached input | $0.16 (best) | — | $0.20 |
| Blended (3:1) | $1.71 | $0.601 (best) | $1.56 |
| Long-context rate | Same rate | Same rate | Over 200K: $2.50 / $5.00 |
| Price source | Official Moonshot AI API | Median of 8 providers | Official xAI API |
| Limits | |||
| Context window | 262,144 tokens | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 262,144 tokens (best) | 8,192 tokens | 30,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | OpenMIT License | Proprietary |
| API model ID | kimi-k2.6 | — | grok-4.20-0309-reasoning |
| API providers | 46 (best) | 8 | 11 |
| Released | Apr 21, 2026 | Aug 21, 2025 | Mar 9, 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 K2.6$17.50
- DeepSeek-V3.1$6.35
- Grok 4.20 (Reasoning)$17.50
Which should you choose?
Which is better: Kimi K2.6, DeepSeek-V3.1 or Grok 4.20 (Reasoning)?
Grok 4.20 (Reasoning) is the better all-round choice, scoring 68/100 against Kimi K2.6 (65) and DeepSeek-V3.1 (55). It leads on context window. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Kimi K2.6, DeepSeek-V3.1 or Grok 4.20 (Reasoning)?
DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). Grok 4.20 (Reasoning) costs $1.25 input / $2.50 output per million tokens (official xAI API price); Kimi K2.6 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 $0.601 per million tokens for DeepSeek-V3.1 versus $1.56 for Grok 4.20 (Reasoning) (2.6× as much) and $1.71 for Kimi K2.6 (2.8× as much).
Which scores higher on benchmarks?
Grok 4.20 (Reasoning) scores higher on the Capabilities Index (ECI): Grok 4.20 (Reasoning) 152.0 (#41 of 148), Kimi K2.6 151.1 (#45 of 148) and DeepSeek-V3.1 139.9 (#100 of 148). The confidence ranges of the top two overlap (149.3–154.4 vs 149.1–152.8), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3.1 and Grok 4.20 (Reasoning) yet, so there is no like-for-like coding score. On overall capability, Grok 4.20 (Reasoning) 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 4.20 (Reasoning) has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2.6 and 131,072 for DeepSeek-V3.1. Maximum output per response: Kimi K2.6 up to 262,144, DeepSeek-V3.1 up to 8,192, Grok 4.20 (Reasoning) up to 30,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K2.6 accepts text, images and video; DeepSeek-V3.1 accepts text; Grok 4.20 (Reasoning) accepts text, images and PDFs. Kimi K2.6 handles the widest range of inputs.
Are any of these open source?
Kimi K2.6 and DeepSeek-V3.1 publishes its weights (MIT License) and can be self-hosted; Grok 4.20 (Reasoning) is proprietary.
Which is newer?
Kimi K2.6 is the newest, released Apr 21, 2026. Grok 4.20 (Reasoning) came out Mar 9, 2026; DeepSeek-V3.1 came out Aug 21, 2025. Knowledge cutoff: Kimi K2.6 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.
