Apertus 70B vs GLM-4.5 vs Morph V3 Large
GLM-4.5 comes out ahead, 39 to 32 and 30 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
Z.ai (Zhipu)GLM-4.5
39/100- ECI—
- Price$0.60 / $2.20
- Context131K
Morph
Morph V3 Large
30/100- ECI—
- Price$0.90 / $1.90
- Context262K
GLM-4.5 is our pick
GLM-4.5 is the better all-round choice, scoring 39/100 against Apertus 70B (32) and Morph V3 Large (30). It leads on price and inputs & features. Morph V3 Large 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 priceGLM-4.5GLM-4.5 $1.00 · Morph V3 Large $1.15 · Apertus 70B $1.22 per 1M tokens (3:1 blend)
- Longest contextMorph V3 LargeMorph V3 Large 262,144 · GLM-4.5 131,072 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsApertus 70B: Text · GLM-4.5: Text · Morph V3 Large: Text
- Self-hostingApertus 70B and GLM-4.5Publishes downloadable weights (Apache-2.0)
| Measure | Weight | Apertus 70B | GLM-4.5 | Morph V3 Large |
|---|---|---|---|---|
| Price | 50% | 44 | 48 | 45 |
| Inputs & features | 30% | 25 | 35 | 0 |
| Context window | 20% | 12 | 25 | 37 |
| Overall | 100% | 32/100 | 39/100 | 30/100 |
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-4.5Z.ai (Zhipu) | Morph V3 LargeMorph |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.82 | $0.60 (best) | $0.90 |
| Output | $2.42 | $2.20 | $1.90 (best) |
| Cached input | — | $0.11 | — |
| Blended (3:1) | $1.22 | $1.00 (best) | $1.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Z.AI API | Median of 5 providers |
| Limits | |||
| Context window | 65,536 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 98,304 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 | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | — | glm-4.5 | — |
| API providers | 3 | 19 (best) | 5 |
| Released | Sep 2, 2025 | Jul 28, 2025 | Jul 7, 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.
- Apertus 70B$13.04
- GLM-4.5$10.40
- Morph V3 Large$12.80
Which should you choose?
Which is better: Apertus 70B, GLM-4.5 or Morph V3 Large?
GLM-4.5 is the better all-round choice, scoring 39/100 against Apertus 70B (32) and Morph V3 Large (30). It leads on price and inputs & features. Morph V3 Large 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, Apertus 70B, GLM-4.5 or Morph V3 Large?
GLM-4.5 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). Morph V3 Large costs $0.90 input / $1.90 output per million tokens (median across 5 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 $1.00 per million tokens for GLM-4.5 versus $1.15 for Morph V3 Large (1.1× 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-4.5 has not been scored yet and Morph V3 Large has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 70B, GLM-4.5 and Morph V3 Large yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Morph V3 Large does not support tool calling, which most coding agents need.
Which has the bigger context window?
Morph V3 Large has the largest context window at 262,144 tokens, against 131,072 for GLM-4.5 and 65,536 for Apertus 70B. Maximum output per response: Apertus 70B up to 8,192, GLM-4.5 up to 98,304, Morph V3 Large up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Apertus 70B accepts text; GLM-4.5 accepts text; Morph V3 Large accepts text. They handle the same number of input types.
Are any of these open source?
Apertus 70B and GLM-4.5 publishes its weights (Apache-2.0) and can be self-hosted; Morph V3 Large is proprietary.
Which is newer?
Apertus 70B is the newest, released Sep 2, 2025. GLM-4.5 came out Jul 28, 2025; Morph V3 Large came out Jul 7, 2025. Knowledge cutoff: Apertus 70B Sep 2025, GLM-4.5 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.
