Gemini 2.0 Flash vs Grok 4.20 (Reasoning) vs Kimi K2.6
Grok 4.20 (Reasoning) comes out ahead, 78 to 74 and 65 on our weighted score, and it is the cheaper option too.
GoogleGemini 2.0 Flash
65/100- ECI134.7
- Price—
- Context1.05M
- Our pick
xAIGrok 4.20 (Reasoning)
78/100- ECI152.0
- Price$1.25 / $2.50
- Context1M
Moonshot AIKimi K2.6
74/100- ECI151.1
- Price$0.95 / $4.00
- Context262K
Grok 4.20 (Reasoning) is our pick
Grok 4.20 (Reasoning) is the better all-round choice, scoring 78/100 against Kimi K2.6 (74) and Gemini 2.0 Flash (65). Gemini 2.0 Flash wins on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityGrok 4.20 (Reasoning)Capabilities Index (ECI): Grok 4.20 (Reasoning) 152.0 · Kimi K2.6 151.1 · Gemini 2.0 Flash 134.7
- Lowest priceGrok 4.20 (Reasoning)Grok 4.20 (Reasoning) $1.56 · Kimi K2.6 $1.71 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
- Longest contextGemini 2.0 FlashGemini 2.0 Flash 1,048,576 · Grok 4.20 (Reasoning) 1,000,000 · Kimi K2.6 262,144 tokens
- Widest inputsGemini 2.0 FlashGemini 2.0 Flash: Text, Images, PDFs, Audio, Video · Grok 4.20 (Reasoning): Text, Images, PDFs · Kimi K2.6: Text, Images, Video
- Self-hostingKimi K2.6Publishes downloadable weights
| Measure | Weight | Gemini 2.0 Flash | Grok 4.20 (Reasoning) | Kimi K2.6 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 59 | 81 | 79 |
| Inputs & features | 20% | 90 | 80 | 80 |
| Context window | 13% | 61 | 60 | 37 |
| Overall | 100% | 65/100 | 78/100 | 74/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.0 FlashGoogle | Grok 4.20 (Reasoning)xAI | Kimi K2.6Moonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 134.7 | 152.0 (best) | 151.1 |
| ECI rank | #116 of 148 | #41 of 148 (best) | #45 of 148 |
| GPQA DiamondGraduate-level science questions | — | 89.3% | 90.8% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 44.9% | 57.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 92.2% | 96.1% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 76.7% |
| SimpleQA VerifiedShort factual questions | — | 30.2% | 34.9% (best) |
| Price per million tokens | |||
| Input | — | $1.25 | $0.95 (best) |
| Output | — | $2.50 (best) | $4.00 |
| Cached input | — | $0.20 | $0.16 (best) |
| Blended (3:1) | — | $1.56 (best) | $1.71 |
| Long-context rate | — | Over 200K: $2.50 / $5.00 | Same rate |
| Price source | — | Official xAI API | Official Moonshot AI API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,000,000 tokens | 262,144 tokens |
| Max output | 8,192 tokens | 30,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | No |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | grok-4.20-0309-reasoning | kimi-k2.6 |
| API providers | — | 11 | 46 (best) |
| Released | Dec 11, 2024 | Mar 9, 2026 | Apr 21, 2026 |
| Knowledge cutoff | Jun 2024 | — | 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.
- Gemini 2.0 Flash—
- Grok 4.20 (Reasoning)$17.50
- Kimi K2.6$17.50
Which should you choose?
Which is better: Gemini 2.0 Flash, Grok 4.20 (Reasoning) or Kimi K2.6?
Grok 4.20 (Reasoning) is the better all-round choice, scoring 78/100 against Kimi K2.6 (74) and Gemini 2.0 Flash (65). Gemini 2.0 Flash wins on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemini 2.0 Flash, Grok 4.20 (Reasoning) or Kimi K2.6?
Grok 4.20 (Reasoning) is cheaper at $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 $1.56 per million tokens for Grok 4.20 (Reasoning) versus $1.71 for Kimi K2.6 (1.1× as much). Gemini 2.0 Flash has no published per-token price.
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 Gemini 2.0 Flash 134.7 (#116 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 Gemini 2.0 Flash 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?
Gemini 2.0 Flash has the largest context window at 1,048,576 tokens, against 1,000,000 for Grok 4.20 (Reasoning) and 262,144 for Kimi K2.6. Maximum output per response: Gemini 2.0 Flash up to 8,192, Grok 4.20 (Reasoning) up to 30,000, Kimi K2.6 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash accepts text, images, PDFs, audio and video; Grok 4.20 (Reasoning) accepts text, images and PDFs; Kimi K2.6 accepts text, images and video. Gemini 2.0 Flash handles the widest range of inputs.
Are any of these open source?
Kimi K2.6 publishes its weights and can be self-hosted; Gemini 2.0 Flash and 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; Gemini 2.0 Flash came out Dec 11, 2024. Knowledge cutoff: Gemini 2.0 Flash Jun 2024, 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.
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