Ring-1T vs Apertus 70B vs GLM-4.6
GLM-4.6 comes out ahead, 42 to 33 and 33 on our weighted score.
inclusionAIRing-1T
33/100- ECI—
- Price$0.57 / $2.29
- Context128K
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
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 priceRing-1T and GLM-4.6Ring-1T $1.00 · GLM-4.6 $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 inputsRing-1T: Text · Apertus 70B: Text · GLM-4.6: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ring-1T | Apertus 70B | GLM-4.6 |
|---|---|---|---|---|
| Price | 50% | 50 | 46 | 50 |
| Inputs & features | 30% | 10 | 25 | 35 |
| Context window | 20% | 24 | 12 | 32 |
| Overall | 100% | 33/100 | 33/100 | 42/100 |
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 | Ring-1TinclusionAI | Apertus 70BSwiss AI | GLM-4.6Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.57 (best) | $0.82 | $0.60 |
| Output | $2.29 | $2.42 | $2.20 (best) |
| Cached input | — | — | $0.11 |
| Blended (3:1) | $1.00 (best) | $1.22 | $1.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Bailing API | Median of 3 providers | Official Z.AI API |
| Limits | |||
| Context window | 128,000 tokens | 65,536 tokens | 204,800 tokens (best) |
| Max output | 32,000 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 | Yes | No | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache-2.0 | Open |
| API model ID | Ring-1T | — | glm-4.6 |
| API providers | 1 | 3 | 18 (best) |
| Released | Oct 2025 | Sep 2, 2025 | Sep 30, 2025 |
| Knowledge cutoff | Jun 2024 | 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.
- Ring-1T$10.28
- Apertus 70B$13.04
- GLM-4.6$10.40
Which should you choose?
Which is better: Ring-1T, Apertus 70B or GLM-4.6?
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, Ring-1T, Apertus 70B or GLM-4.6?
Ring-1T is cheaper at $0.57 input / $2.29 output per million tokens (official Bailing API price). 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 $1.00 per million tokens for Ring-1T versus $1.00 for GLM-4.6 (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. Ring-1T 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 Ring-1T, 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 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: Ring-1T up to 32,000, Apertus 70B up to 8,192, GLM-4.6 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Ring-1T 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?
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: Ring-1T Jun 2024, 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 Oct 4, 2026.
