Apertus 70B vs Kimi K2 Instruct 0905 vs Relace Search
Kimi K2 Instruct 0905 comes out ahead, 38 to 35 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
Moonshot AIKimi K2 Instruct 0905
38/100- ECI—
- Price$0.60 / $2.50
- Context262K
Relace
Relace Search
35/100- ECI—
- Price$1.00 / $3.00
- Context256K
Kimi K2 Instruct 0905 is our pick
Kimi K2 Instruct 0905 is the better all-round choice, scoring 38/100 against Relace Search (35) and Apertus 70B (32). It leads on price. 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 priceKimi K2 Instruct 0905Kimi K2 Instruct 0905 $1.07 · Apertus 70B $1.22 · Relace Search $1.50 per 1M tokens (3:1 blend)
- Longest contextKimi K2 Instruct 0905Kimi K2 Instruct 0905 262,144 · Relace Search 256,000 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsApertus 70B: Text · Kimi K2 Instruct 0905: Text · Relace Search: Text
- Self-hostingApertus 70B and Kimi K2 Instruct 0905Publishes downloadable weights (Apache-2.0 and Modified MIT)
| Measure | Weight | Apertus 70B | Kimi K2 Instruct 0905 | Relace Search |
|---|---|---|---|---|
| Price | 50% | 44 | 46 | 40 |
| Inputs & features | 30% | 25 | 25 | 25 |
| Context window | 20% | 12 | 37 | 36 |
| Overall | 100% | 32/100 | 38/100 | 35/100 |
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 | Kimi K2 Instruct 0905Moonshot AI | Relace SearchRelace |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.82 | $0.60 (best) | $1.00 |
| Output | $2.42 (best) | $2.50 | $3.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.22 | $1.07 (best) | $1.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 12 providers | Median of 3 providers |
| Limits | |||
| Context window | 65,536 tokens | 262,144 tokens (best) | 256,000 tokens |
| Max output | 8,192 tokens | 98,304 tokens | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | OpenModified MIT | Proprietary |
| API model ID | — | — | — |
| API providers | 3 | 13 (best) | 3 |
| Released | Sep 2, 2025 | Sep 5, 2025 | Dec 8, 2025 |
| Knowledge cutoff | Sep 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
- Kimi K2 Instruct 0905$11.00
- Relace Search$16.00
Which should you choose?
Which is better: Apertus 70B, Kimi K2 Instruct 0905 or Relace Search?
Kimi K2 Instruct 0905 is the better all-round choice, scoring 38/100 against Relace Search (35) and Apertus 70B (32). It leads on price. 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, Kimi K2 Instruct 0905 or Relace Search?
Kimi K2 Instruct 0905 is cheaper at $0.60 input / $2.50 output per million tokens (median across 12 API providers). Apertus 70B costs $0.82 input / $2.42 output per million tokens (median across 3 API providers); Relace Search costs $1.00 input / $3.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $1.07 per million tokens for Kimi K2 Instruct 0905 versus $1.22 for Apertus 70B (1.1× as much) and $1.50 for Relace Search (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, Kimi K2 Instruct 0905 has not been scored yet and Relace Search has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 70B, Kimi K2 Instruct 0905 and Relace Search 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?
Kimi K2 Instruct 0905 has the largest context window at 262,144 tokens, against 256,000 for Relace Search and 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, Kimi K2 Instruct 0905 up to 98,304, Relace Search up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Apertus 70B accepts text; Kimi K2 Instruct 0905 accepts text; Relace Search accepts text. They handle the same number of input types.
Are any of these open source?
Apertus 70B and Kimi K2 Instruct 0905 publishes its weights (Apache-2.0 and Modified MIT) and can be self-hosted; Relace Search is proprietary.
Which is newer?
Relace Search is the newest, released Dec 8, 2025. Kimi K2 Instruct 0905 came out Sep 5, 2025; Apertus 70B came out Sep 2, 2025. Knowledge cutoff: Apertus 70B Sep 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.
