Apertus 70B vs GLM-4.6 vs Ring-1T
GLM-4.6 comes out ahead, 42 to 33 and 33 on our weighted score.
Swiss AI
Apertus 70B
33/100- ECI—
- Price$0.82 / $2.42
- Context66K
- Our pick
Z.ai (Zhipu)GLM-4.6
42/100- ECI—
- Price$0.60 / $2.20
- Context205K
inclusionAIRing-1T
33/100- ECI—
- Price$0.57 / $2.29
- Context128K
GLM-4.6 is our pick
GLM-4.6 is the better all-round choice, scoring 42/100 against Apertus 70B (33) and Ring-1T (33). It leads on 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 priceGLM-4.6 and Ring-1TGLM-4.6 $1.00 · Ring-1T $1.00 · Apertus 70B $1.22 per 1M tokens (3:1 blend)
- Longest contextGLM-4.6GLM-4.6 204,800 · Ring-1T 128,000 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsApertus 70B: Text · GLM-4.6: Text · Ring-1T: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Apertus 70B | GLM-4.6 | Ring-1T |
|---|---|---|---|---|
| Price | 50% | 46 | 50 | 50 |
| Inputs & features | 30% | 25 | 35 | 10 |
| Context window | 20% | 12 | 32 | 24 |
| Overall | 100% | 33/100 | 42/100 | 33/100 |
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 | GLM-4.6Z.ai (Zhipu) | Ring-1TinclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.82 | $0.60 | $0.57 (best) |
| Output | $2.42 | $2.20 (best) | $2.29 |
| Cached input | — | $0.11 | — |
| Blended (3:1) | $1.22 | $1.00 (best) | $1.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Z.AI API | Official Bailing API |
| Limits | |||
| Context window | 65,536 tokens | 204,800 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 131,072 tokens (best) | 32,000 tokens |
| 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 | Yes | Yes |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Open |
| API model ID | — | glm-4.6 | Ring-1T |
| API providers | 3 | 18 (best) | 1 |
| Released | Sep 2, 2025 | Sep 30, 2025 | Oct 2025 |
| Knowledge cutoff | Sep 2025 | Apr 2025 | Jun 2024 |
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
- GLM-4.6$10.40
- Ring-1T$10.28
Which should you choose?
Which is better: Apertus 70B, GLM-4.6 or Ring-1T?
GLM-4.6 is the better all-round choice, scoring 42/100 against Apertus 70B (33) and Ring-1T (33). It leads on 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, GLM-4.6 or Ring-1T?
GLM-4.6 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). Ring-1T costs $0.57 input / $2.29 output per million tokens (official Bailing 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 $1.00 per million tokens for GLM-4.6 versus $1.00 for Ring-1T (1× as much) and $1.22 for Apertus 70B (1.2× 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, GLM-4.6 has not been scored yet and Ring-1T has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 70B, GLM-4.6 and Ring-1T yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Ring-1T does not support tool calling, which most coding agents need.
Which has the bigger context window?
GLM-4.6 has the largest context window at 204,800 tokens, against 128,000 for Ring-1T and 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, GLM-4.6 up to 131,072, Ring-1T up to 32,000 tokens.
Which can read images, PDFs, audio or video?
Apertus 70B accepts text; GLM-4.6 accepts text; Ring-1T accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Ring-1T is the newest, released Oct 2025. GLM-4.6 came out Sep 30, 2025; Apertus 70B came out Sep 2, 2025. Knowledge cutoff: Apertus 70B Sep 2025, GLM-4.6 Apr 2025, Ring-1T Jun 2024.
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.
