GLM-4.5V vs Qwen-VL OCR vs Qwen3-Next 80B-A3B Instruct
GLM-4.5V comes out ahead, 49 to 39 and 36 on our weighted score, though Qwen-VL OCR is 20% cheaper per token.
- Our pick
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
Alibaba (Qwen)Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
- Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
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 Qwen-VL OCR (36). It leads on inputs & features. Qwen-VL OCR wins on price. Qwen3-Next 80B-A3B Instruct 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 priceQwen-VL OCRQwen-VL OCR $0.72 · 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 · GLM-4.5V 64,000 · Qwen-VL OCR 34,096 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Qwen-VL OCR: Text, Images · Qwen3-Next 80B-A3B Instruct: Text
- Self-hostingGLM-4.5V and Qwen3-Next 80B-A3B InstructPublishes downloadable weights
| Measure | Weight | GLM-4.5V | Qwen-VL OCR | Qwen3-Next 80B-A3B Instruct |
|---|---|---|---|---|
| Price | 50% | 52 | 57 | 53 |
| Inputs & features | 30% | 70 | 25 | 25 |
| Context window | 20% | 12 | 1 | 24 |
| Overall | 100% | 49/100 | 36/100 | 39/100 |
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 | GLM-4.5VZ.ai (Zhipu) | Qwen-VL OCRAlibaba (Qwen) | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.72 | $0.50 (best) |
| Output | $1.80 | $0.72 (best) | $2.00 |
| Cached input | — | — | — |
| Blended (3:1) | $0.90 | $0.72 (best) | $0.875 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 64,000 tokens | 34,096 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens | 4,096 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.5v | qwen-vl-ocr | qwen3-next-80b-a3b-instruct |
| API providers | 11 | 1 | 13 (best) |
| Released | Aug 11, 2025 | Oct 28, 2024 | Sep 2025 |
| Knowledge cutoff | Apr 2025 | Apr 2024 | 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.
- GLM-4.5V$9.60
- Qwen-VL OCR$8.64
- Qwen3-Next 80B-A3B Instruct$9.00
Which should you choose?
Which is better: GLM-4.5V, Qwen-VL OCR or Qwen3-Next 80B-A3B Instruct?
GLM-4.5V is the better all-round choice, scoring 49/100 against Qwen3-Next 80B-A3B Instruct (39) and Qwen-VL OCR (36). It leads on inputs & features. Qwen-VL OCR wins on price. Qwen3-Next 80B-A3B Instruct 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, GLM-4.5V, Qwen-VL OCR or Qwen3-Next 80B-A3B Instruct?
Qwen-VL OCR is cheaper at $0.72 input / $0.72 output per million tokens (official Alibaba API price). 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 $0.72 per million tokens for Qwen-VL OCR versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.2× as much) and $0.90 for GLM-4.5V (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5V has not been scored yet, Qwen-VL OCR has not been scored yet and Qwen3-Next 80B-A3B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V, Qwen-VL OCR and Qwen3-Next 80B-A3B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR 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 64,000 for GLM-4.5V and 34,096 for Qwen-VL OCR. Maximum output per response: GLM-4.5V up to 16,384, Qwen-VL OCR up to 4,096, Qwen3-Next 80B-A3B Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; Qwen-VL OCR accepts text and images; Qwen3-Next 80B-A3B Instruct accepts text. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V and Qwen3-Next 80B-A3B Instruct publishes its weights and can be self-hosted; Qwen-VL OCR is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GLM-4.5V came out Aug 11, 2025; Qwen-VL OCR came out Oct 28, 2024. Knowledge cutoff: GLM-4.5V Apr 2025, Qwen-VL OCR Apr 2024, Qwen3-Next 80B-A3B Instruct 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.
