Qwen3-Next 80B-A3B (Thinking) vs GLM-5-Turbo vs Apertus 70B
GLM-5-Turbo comes out ahead, 38 to 34 and 33 on our weighted score, though Apertus 70B is 36% cheaper per token.
Alibaba (Qwen)Qwen3-Next 80B-A3B (Thinking)
34/100- ECI—
- Price$0.50 / $6.00
- Context131K
- Our pick
Z.ai (Zhipu)GLM-5-Turbo
38/100- ECI—
- Price$1.20 / $4.00
- Context200K
Swiss AI
Apertus 70B
33/100- ECI—
- Price$0.82 / $2.42
- Context66K
GLM-5-Turbo is our pick
GLM-5-Turbo is the better all-round choice, scoring 38/100 against Qwen3-Next 80B-A3B (Thinking) (34) and Apertus 70B (33). It leads on inputs & features and context window. Apertus 70B wins 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 priceApertus 70BApertus 70B $1.22 · Qwen3-Next 80B-A3B (Thinking) $1.88 · GLM-5-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextGLM-5-TurboGLM-5-Turbo 200,000 · Qwen3-Next 80B-A3B (Thinking) 131,072 · Apertus 70B 65,536 tokens
- Widest inputsSame inputsQwen3-Next 80B-A3B (Thinking): Text · GLM-5-Turbo: Text · Apertus 70B: Text
- Self-hostingQwen3-Next 80B-A3B (Thinking) and Apertus 70BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3-Next 80B-A3B (Thinking) | GLM-5-Turbo | Apertus 70B |
|---|---|---|---|---|
| Price | 50% | 37 | 37 | 46 |
| Inputs & features | 30% | 35 | 45 | 25 |
| Context window | 20% | 24 | 32 | 12 |
| Overall | 100% | 34/100 | 38/100 | 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 | Qwen3-Next 80B-A3B (Thinking)Alibaba (Qwen) | GLM-5-TurboZ.ai (Zhipu) | Apertus 70BSwiss AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 (best) | $1.20 | $0.82 |
| Output | $6.00 | $4.00 | $2.42 (best) |
| Cached input | — | $0.24 | — |
| Blended (3:1) | $1.88 | $1.90 | $1.22 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Z.AI API | Median of 3 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 65,536 tokens |
| Max output | 32,768 tokens | 131,072 tokens (best) | 8,192 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 | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | qwen3-next-80b-a3b-thinking | glm-5-turbo | — |
| API providers | 10 | 17 (best) | 3 |
| Released | Sep 2025 | Mar 16, 2026 | Sep 2, 2025 |
| Knowledge cutoff | Apr 2025 | — | 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.
- Qwen3-Next 80B-A3B (Thinking)$17.00
- GLM-5-Turbo$20.00
- Apertus 70B$13.04
Which should you choose?
Which is better: Qwen3-Next 80B-A3B (Thinking), GLM-5-Turbo or Apertus 70B?
GLM-5-Turbo is the better all-round choice, scoring 38/100 against Qwen3-Next 80B-A3B (Thinking) (34) and Apertus 70B (33). It leads on inputs & features and context window. Apertus 70B wins 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, Qwen3-Next 80B-A3B (Thinking), GLM-5-Turbo or Apertus 70B?
Apertus 70B is cheaper at $0.82 input / $2.42 output per million tokens (median across 3 API providers). Qwen3-Next 80B-A3B (Thinking) costs $0.50 input / $6.00 output per million tokens (official Alibaba API price); GLM-5-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.22 per million tokens for Apertus 70B versus $1.88 for Qwen3-Next 80B-A3B (Thinking) (1.5× as much) and $1.90 for GLM-5-Turbo (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-Next 80B-A3B (Thinking) has not been scored yet, GLM-5-Turbo has not been scored yet and Apertus 70B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3-Next 80B-A3B (Thinking), GLM-5-Turbo and Apertus 70B 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?
GLM-5-Turbo has the largest context window at 200,000 tokens, against 131,072 for Qwen3-Next 80B-A3B (Thinking) and 65,536 for Apertus 70B. Maximum output per response: Qwen3-Next 80B-A3B (Thinking) up to 32,768, GLM-5-Turbo up to 131,072, Apertus 70B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B (Thinking) accepts text; GLM-5-Turbo accepts text; Apertus 70B accepts text. They handle the same number of input types.
Are any of these open source?
Qwen3-Next 80B-A3B (Thinking) and Apertus 70B publishes its weights (Apache-2.0) and can be self-hosted; GLM-5-Turbo is proprietary.
Which is newer?
GLM-5-Turbo is the newest, released Mar 16, 2026. Apertus 70B came out Sep 2, 2025; Qwen3-Next 80B-A3B (Thinking) came out Sep 2025. Knowledge cutoff: Qwen3-Next 80B-A3B (Thinking) Apr 2025, 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 Oct 4, 2026.
