Relace Apply 3 vs Apertus 70B vs GLM-4.6
GLM-4.6 comes out ahead, 41 to 32 and 32 on our weighted score, though Relace Apply 3 is 5% cheaper per token.
Relace
Relace Apply 3
32/100- ECI—
- Price$0.85 / $1.25
- Context256K
Swiss AI
Apertus 70B
32/100- ECI—
- Price$0.82 / $2.42
- Context66K
- Our pick
Z.ai (Zhipu)GLM-4.6
41/100- ECI—
- Price$0.60 / $2.20
- Context205K
GLM-4.6 is our pick
GLM-4.6 is the better all-round choice, scoring 41/100 against Apertus 70B (32) and Relace Apply 3 (32). It leads on inputs & features. Relace Apply 3 wins on 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 priceRelace Apply 3Relace Apply 3 $0.95 · GLM-4.6 $1.00 · Apertus 70B $1.22 per 1M tokens (3:1 blend)
- Longest contextRelace Apply 3Relace Apply 3 256,000 · GLM-4.6 204,800 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsRelace Apply 3: Text · Apertus 70B: Text · GLM-4.6: Text
- Self-hostingApertus 70B and GLM-4.6Publishes downloadable weights (Apache-2.0)
| Measure | Weight | Relace Apply 3 | Apertus 70B | GLM-4.6 |
|---|---|---|---|---|
| Price | 50% | 49 | 44 | 48 |
| Inputs & features | 30% | 0 | 25 | 35 |
| Context window | 20% | 36 | 12 | 32 |
| Overall | 100% | 32/100 | 32/100 | 41/100 |
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 | Relace Apply 3Relace | Apertus 70BSwiss AI | GLM-4.6Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.85 | $0.82 | $0.60 (best) |
| Output | $1.25 (best) | $2.42 | $2.20 |
| Cached input | — | — | $0.11 |
| Blended (3:1) | $0.95 (best) | $1.22 | $1.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 3 providers | Official Z.AI API |
| Limits | |||
| Context window | 256,000 tokens (best) | 65,536 tokens | 204,800 tokens |
| Max output | 128,000 tokens | 8,192 tokens | 131,072 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 | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache-2.0 | Open |
| API model ID | — | — | glm-4.6 |
| API providers | 3 | 3 | 29 (best) |
| Released | Sep 26, 2025 | Sep 2, 2025 | Sep 30, 2025 |
| Knowledge cutoff | — | Sep 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Relace Apply 3$11.00
- Apertus 70B$13.04
- GLM-4.6$10.40
Which should you choose?
Which is better: Relace Apply 3, Apertus 70B or GLM-4.6?
GLM-4.6 is the better all-round choice, scoring 41/100 against Apertus 70B (32) and Relace Apply 3 (32). It leads on inputs & features. Relace Apply 3 wins on 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, Relace Apply 3, Apertus 70B or GLM-4.6?
Relace Apply 3 is cheaper at $0.85 input / $1.25 output per million tokens (median across 3 API providers). GLM-4.6 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price); 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 $0.95 per million tokens for Relace Apply 3 versus $1.00 for GLM-4.6 (1.1× as much) and $1.22 for Apertus 70B (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Relace Apply 3 has not been scored yet, Apertus 70B has not been scored yet and GLM-4.6 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Relace Apply 3, Apertus 70B and GLM-4.6 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Relace Apply 3 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Relace Apply 3 has the largest context window at 256,000 tokens, against 204,800 for GLM-4.6 and 65,536 for Apertus 70B. Maximum output per response: Relace Apply 3 up to 128,000, Apertus 70B up to 8,192, GLM-4.6 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Relace Apply 3 accepts text; Apertus 70B accepts text; GLM-4.6 accepts text. They handle the same number of input types.
Are any of these open source?
Apertus 70B and GLM-4.6 publishes its weights (Apache-2.0) and can be self-hosted; Relace Apply 3 is proprietary.
Which is newer?
GLM-4.6 is the newest, released Sep 30, 2025. Relace Apply 3 came out Sep 26, 2025; Apertus 70B came out Sep 2, 2025. Knowledge cutoff: Apertus 70B Sep 2025, GLM-4.6 Apr 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.
