Qwen3-Next 80B-A3B Instruct vs Morph V3 Fast vs GLM-4.5V
GLM-4.5V comes out ahead, 48 to 40 and 32 on our weighted score.
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
40/100- ECI—
- Price$0.50 / $2.00
- Context262K
Morph
Morph V3 Fast
32/100- ECI—
- Price$0.80 / $1.20
- Context262K
- Our pick
Z.ai (Zhipu)GLM-4.5V
48/100- ECI—
- Price$0.60 / $1.80
- Context64K
GLM-4.5V is our pick
GLM-4.5V is the better all-round choice, scoring 48/100 against Qwen3-Next 80B-A3B Instruct (40) and Morph V3 Fast (32). It leads on inputs & features. 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 priceQwen3-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct $0.875 · Morph V3 Fast $0.90 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextQwen3-Next 80B-A3B Instruct and Morph V3 FastQwen3-Next 80B-A3B Instruct 262,144 · Morph V3 Fast 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VQwen3-Next 80B-A3B Instruct: Text · Morph V3 Fast: Text · GLM-4.5V: Text, Images, Video
- Self-hostingQwen3-Next 80B-A3B Instruct and GLM-4.5VPublishes downloadable weights
| Measure | Weight | Qwen3-Next 80B-A3B Instruct | Morph V3 Fast | GLM-4.5V |
|---|---|---|---|---|
| Price | 50% | 50 | 50 | 50 |
| Inputs & features | 30% | 25 | 0 | 70 |
| Context window | 20% | 37 | 37 | 12 |
| Overall | 100% | 40/100 | 32/100 | 48/100 |
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) | Morph V3 FastMorph | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 (best) | $0.80 | $0.60 |
| Output | $2.00 | $1.20 (best) | $1.80 |
| Cached input | — | — | $0.11 |
| Blended (3:1) | $0.875 (best) | $0.90 | $0.90 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 5 providers | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 64,000 tokens |
| Max output | 32,768 tokens | 131,072 tokens (best) | 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 | Proprietary | Open |
| API model ID | qwen3-next-80b-a3b-instruct | — | glm-4.5v |
| API providers | 18 (best) | 5 | 17 |
| Released | Sep 2025 | Jul 7, 2025 | 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
- Morph V3 Fast$10.40
- GLM-4.5V$9.60
Which should you choose?
Which is better: Qwen3-Next 80B-A3B Instruct, Morph V3 Fast or GLM-4.5V?
GLM-4.5V is the better all-round choice, scoring 48/100 against Qwen3-Next 80B-A3B Instruct (40) and Morph V3 Fast (32). It leads on inputs & features. 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, Morph V3 Fast or GLM-4.5V?
Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 input / $2.00 output per million tokens (official Alibaba API price). Morph V3 Fast costs $0.80 input / $1.20 output per million tokens (median across 5 API providers); 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 $0.875 per million tokens for Qwen3-Next 80B-A3B Instruct versus $0.90 for Morph V3 Fast (1× as much) and $0.90 for GLM-4.5V (1× 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, Morph V3 Fast 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, Morph V3 Fast 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 Morph V3 Fast does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct and Morph V3 Fast have the largest context windows (262,144 and 262,144 tokens), against 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Next 80B-A3B Instruct up to 32,768, Morph V3 Fast up to 131,072, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B Instruct accepts text; Morph V3 Fast 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?
Qwen3-Next 80B-A3B Instruct and GLM-4.5V publishes its weights and can be self-hosted; Morph V3 Fast is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GLM-4.5V came out Aug 11, 2025; Morph V3 Fast came out Jul 7, 2025. 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 Nov 2, 2026.
