Gemini 2.5 Flash vs Kimi K2 Instruct vs Kimi K2 Instruct 0905
Gemini 2.5 Flash comes out ahead, 68 to 38 and 36 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.5 Flash
68/100- ECI140.6
- Price$0.30 / $2.50
- Context1.05M
Moonshot AIKimi K2 Instruct
36/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
- Moonshot AI
Kimi K2 Instruct 0905
38/100- ECI—
- Price$0.60 / $2.50
- Context262K
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against Kimi K2 Instruct 0905 (38) and Kimi K2 Instruct (36). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGemini 2.5 FlashGemini 2.5 Flash $0.85 · Kimi K2 Instruct $1.00 · Kimi K2 Instruct 0905 $1.07 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · Kimi K2 Instruct 0905 262,144 · Kimi K2 Instruct 131,072 tokens
- Widest inputsGemini 2.5 FlashGemini 2.5 Flash: Text, Images, PDFs, Audio, Video · Kimi K2 Instruct: Text · Kimi K2 Instruct 0905: Text
- Self-hostingKimi K2 Instruct and Kimi K2 Instruct 0905Publishes downloadable weights (Modified MIT)
| Measure | Weight | Gemini 2.5 Flash | Kimi K2 Instruct | Kimi K2 Instruct 0905 |
|---|---|---|---|---|
| Price | 50% | 51 | 48 | 46 |
| Inputs & features | 30% | 100 | 25 | 25 |
| Context window | 20% | 61 | 25 | 37 |
| Overall | 100% | 68/100 | 36/100 | 38/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 FlashGoogle | Kimi K2 InstructMoonshot AI | Kimi K2 Instruct 0905Moonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 140.6 (best) | 139.9 | — |
| ECI rank | #110 of 165 (best) | #112 of 165 | — |
| Price per million tokens | |||
| Input | $0.30 (best) | $0.57 | $0.60 |
| Output | $2.50 | $2.30 (best) | $2.50 |
| Cached input | $0.03 | — | — |
| Blended (3:1) | $0.85 (best) | $1.00 | $1.07 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Median of 11 providers | Median of 12 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 32,768 tokens | 98,304 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenModified MIT | OpenModified MIT |
| API model ID | gemini-2.5-flash | — | — |
| API providers | 32 (best) | 11 | 13 |
| Released | Jun 17, 2025 | Jul 11, 2025 | Sep 5, 2025 |
| 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.
- Gemini 2.5 Flash$8.00
- Kimi K2 Instruct$10.30
- Kimi K2 Instruct 0905$11.00
Which should you choose?
Which is better: Gemini 2.5 Flash, Kimi K2 Instruct or Kimi K2 Instruct 0905?
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against Kimi K2 Instruct 0905 (38) and Kimi K2 Instruct (36). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemini 2.5 Flash, Kimi K2 Instruct or Kimi K2 Instruct 0905?
Gemini 2.5 Flash is cheaper at $0.30 input / $2.50 output per million tokens (official Google API price). Kimi K2 Instruct costs $0.57 input / $2.30 output per million tokens (median across 11 API providers); Kimi K2 Instruct 0905 costs $0.60 input / $2.50 output per million tokens (median across 12 API providers). At a typical mix of three input tokens to one output token, that is $0.85 per million tokens for Gemini 2.5 Flash versus $1.00 for Kimi K2 Instruct (1.2× as much) and $1.07 for Kimi K2 Instruct 0905 (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash has an ECI of 140.6, Kimi K2 Instruct has an ECI of 139.9 and Kimi K2 Instruct 0905 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash, Kimi K2 Instruct and Kimi K2 Instruct 0905 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash has the largest context window at 1,048,576 tokens, against 262,144 for Kimi K2 Instruct 0905 and 131,072 for Kimi K2 Instruct. Maximum output per response: Gemini 2.5 Flash up to 65,536, Kimi K2 Instruct up to 32,768, Kimi K2 Instruct 0905 up to 98,304 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash accepts text, images, PDFs, audio and video; Kimi K2 Instruct accepts text; Kimi K2 Instruct 0905 accepts text. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
Kimi K2 Instruct and Kimi K2 Instruct 0905 publishes its weights (Modified MIT) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
Kimi K2 Instruct 0905 is the newest, released Sep 5, 2025. Kimi K2 Instruct came out Jul 11, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash 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 Nov 2, 2026.
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