GLM-4.5V vs GPT-4.1 mini vs Qwen3-Next 80B-A3B Instruct
GPT-4.1 mini comes out ahead, 62 to 49 and 39 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
- Our pick
OpenAIGPT-4.1 mini
62/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 62/100 against GLM-4.5V (49) and Qwen3-Next 80B-A3B Instruct (39). It leads on price and 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 priceGPT-4.1 miniGPT-4.1 mini $0.70 · Qwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Qwen3-Next 80B-A3B Instruct 131,072 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5V and GPT-4.1 miniGLM-4.5V: Text, Images, Video · GPT-4.1 mini: Text, Images, PDFs · Qwen3-Next 80B-A3B Instruct: Text
- Self-hostingGLM-4.5V and Qwen3-Next 80B-A3B InstructPublishes downloadable weights
| Measure | Weight | GLM-4.5V | GPT-4.1 mini | Qwen3-Next 80B-A3B Instruct |
|---|---|---|---|---|
| Price | 50% | 52 | 57 | 53 |
| Inputs & features | 30% | 70 | 70 | 25 |
| Context window | 20% | 12 | 61 | 24 |
| Overall | 100% | 49/100 | 62/100 | 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) | GPT-4.1 miniOpenAI | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 135.0 | — |
| ECI rank | — | #115 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 65.9% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 44.7% | — |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | $0.60 | $0.40 (best) | $0.50 |
| Output | $1.80 | $1.60 (best) | $2.00 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.90 | $0.70 (best) | $0.875 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 64,000 tokens | 1,047,576 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 32,768 tokens (best) | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.5v | gpt-4.1-mini | qwen3-next-80b-a3b-instruct |
| API providers | 11 | 24 (best) | 13 |
| Released | Aug 11, 2025 | Apr 14, 2025 | 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
- GPT-4.1 mini$7.20
- Qwen3-Next 80B-A3B Instruct$9.00
Which should you choose?
Which is better: GLM-4.5V, GPT-4.1 mini or Qwen3-Next 80B-A3B Instruct?
GPT-4.1 mini is the better all-round choice, scoring 62/100 against GLM-4.5V (49) and Qwen3-Next 80B-A3B Instruct (39). It leads on price and 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, GPT-4.1 mini or Qwen3-Next 80B-A3B Instruct?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI 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 $0.70 per million tokens for GPT-4.1 mini versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.3× 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, GPT-4.1 mini has an ECI of 135.0 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, GPT-4.1 mini 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. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 131,072 for Qwen3-Next 80B-A3B Instruct and 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, GPT-4.1 mini up to 32,768, 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; GPT-4.1 mini accepts text, images and PDFs; 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; GPT-4.1 mini is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GLM-4.5V came out Aug 11, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GLM-4.5V Apr 2025, GPT-4.1 mini 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.
