Qwen3-Next 80B-A3B Instruct vs Aya Expanse 32B vs GLM-4.5V
GLM-4.5V comes out ahead, 49 to 39 and 33 on our weighted score, though Aya Expanse 32B is 17% cheaper per token.
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
CohereAya Expanse 32B
33/100- ECI—
- Price$0.50 / $1.50
- Context128K
- Our pick
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
GLM-4.5V is our pick
GLM-4.5V is the better all-round choice, scoring 49/100 against Qwen3-Next 80B-A3B Instruct (39) and Aya Expanse 32B (33). It leads on inputs & features. Aya Expanse 32B 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 priceAya Expanse 32BAya Expanse 32B $0.75 · Qwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextQwen3-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct 131,072 · Aya Expanse 32B 128,000 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VQwen3-Next 80B-A3B Instruct: Text · Aya Expanse 32B: Text · GLM-4.5V: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3-Next 80B-A3B Instruct | Aya Expanse 32B | GLM-4.5V |
|---|---|---|---|---|
| Price | 50% | 53 | 56 | 52 |
| Inputs & features | 30% | 25 | 0 | 70 |
| Context window | 20% | 24 | 24 | 12 |
| Overall | 100% | 39/100 | 33/100 | 49/100 |
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 InstructAlibaba (Qwen) | Aya Expanse 32BCohere | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 (best) | $0.50 (best) | $0.60 |
| Output | $2.00 | $1.50 (best) | $1.80 |
| Cached input | — | — | — |
| Blended (3:1) | $0.875 | $0.75 (best) | $0.90 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 1 providers | Official Z.AI API |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 64,000 tokens |
| Max output | 32,768 tokens (best) | 4,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | No | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenCC-BY-NC-4.0 | Open |
| API model ID | qwen3-next-80b-a3b-instruct | c4ai-aya-expanse-32b | glm-4.5v |
| API providers | 13 (best) | 2 | 11 |
| Released | Sep 2025 | Oct 24, 2024 | Aug 11, 2025 |
| Knowledge cutoff | Apr 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.
- Qwen3-Next 80B-A3B Instruct$9.00
- Aya Expanse 32B$8.00
- GLM-4.5V$9.60
Which should you choose?
Which is better: Qwen3-Next 80B-A3B Instruct, Aya Expanse 32B or GLM-4.5V?
GLM-4.5V is the better all-round choice, scoring 49/100 against Qwen3-Next 80B-A3B Instruct (39) and Aya Expanse 32B (33). It leads on inputs & features. Aya Expanse 32B 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 Instruct, Aya Expanse 32B or GLM-4.5V?
Aya Expanse 32B is cheaper at $0.50 input / $1.50 output per million tokens (median across 1 API provider). Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price); GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Aya Expanse 32B versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.2× as much) and $0.90 for GLM-4.5V (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-Next 80B-A3B Instruct has not been scored yet, Aya Expanse 32B has not been scored yet and GLM-4.5V has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3-Next 80B-A3B Instruct, Aya Expanse 32B and GLM-4.5V yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Expanse 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct has the largest context window at 131,072 tokens, against 128,000 for Aya Expanse 32B and 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Next 80B-A3B Instruct up to 32,768, Aya Expanse 32B up to 4,000, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B Instruct accepts text; Aya Expanse 32B accepts text; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (CC-BY-NC-4.0), so you can self-host them.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GLM-4.5V came out Aug 11, 2025; Aya Expanse 32B came out Oct 24, 2024. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, GLM-4.5V 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.
