Apertus 70B vs Gemini 2.5 Flash vs Kimi K2 Instruct
Gemini 2.5 Flash comes out ahead, 68 to 36 and 32 on our weighted score, and it is the cheaper option too.
Swiss AI
Apertus 70B
32/100- ECI—
- Price$0.82 / $2.42
- Context66K
- 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
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against Kimi K2 Instruct (36) and Apertus 70B (32). 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 · Apertus 70B $1.22 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 FlashGemini 2.5 Flash 1,048,576 · Kimi K2 Instruct 131,072 · Apertus 70B 65,536 tokens
- Widest inputsGemini 2.5 FlashApertus 70B: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · Kimi K2 Instruct: Text
- Self-hostingApertus 70B and Kimi K2 InstructPublishes downloadable weights (Apache-2.0 and Modified MIT)
| Measure | Weight | Apertus 70B | Gemini 2.5 Flash | Kimi K2 Instruct |
|---|---|---|---|---|
| Price | 50% | 44 | 51 | 48 |
| Inputs & features | 30% | 25 | 100 | 25 |
| Context window | 20% | 12 | 61 | 25 |
| Overall | 100% | 32/100 | 68/100 | 36/100 |
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 | Apertus 70BSwiss AI | Gemini 2.5 FlashGoogle | Kimi K2 InstructMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 140.6 (best) | 139.9 |
| ECI rank | — | #110 of 165 (best) | #112 of 165 |
| Price per million tokens | |||
| Input | $0.82 | $0.30 (best) | $0.57 |
| Output | $2.42 | $2.50 | $2.30 (best) |
| Cached input | — | $0.03 | — |
| Blended (3:1) | $1.22 | $0.85 (best) | $1.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Google API | Median of 11 providers |
| Limits | |||
| Context window | 65,536 tokens | 1,048,576 tokens (best) | 131,072 tokens |
| Max output | 8,192 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | OpenModified MIT |
| API model ID | — | gemini-2.5-flash | — |
| API providers | 3 | 32 (best) | 11 |
| Released | Sep 2, 2025 | Jun 17, 2025 | Jul 11, 2025 |
| Knowledge cutoff | Sep 2025 | 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.
- Apertus 70B$13.04
- Gemini 2.5 Flash$8.00
- Kimi K2 Instruct$10.30
Which should you choose?
Which is better: Apertus 70B, Gemini 2.5 Flash or Kimi K2 Instruct?
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against Kimi K2 Instruct (36) and Apertus 70B (32). 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, Apertus 70B, Gemini 2.5 Flash or Kimi K2 Instruct?
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); Apertus 70B costs $0.82 input / $2.42 output per million tokens (median across 3 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 $1.22 for Apertus 70B (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Apertus 70B has not been scored yet, Gemini 2.5 Flash has an ECI of 140.6 and Kimi K2 Instruct has an ECI of 139.9.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 70B, Gemini 2.5 Flash and Kimi K2 Instruct 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 131,072 for Kimi K2 Instruct and 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, Gemini 2.5 Flash up to 65,536, Kimi K2 Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Apertus 70B accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; Kimi K2 Instruct accepts text. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
Apertus 70B and Kimi K2 Instruct publishes its weights (Apache-2.0 and Modified MIT) and can be self-hosted; Gemini 2.5 Flash is proprietary.
Which is newer?
Apertus 70B is the newest, released Sep 2, 2025. Kimi K2 Instruct came out Jul 11, 2025; Gemini 2.5 Flash came out Jun 17, 2025. Knowledge cutoff: Apertus 70B Sep 2025, 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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