GLM-4.5V vs GPT-4.1 mini vs Qwen3-Coder 30B-A3B Instruct
GPT-4.1 mini comes out ahead, 62 to 49 and 41 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-Coder 30B-A3B Instruct
41/100- ECI—
- Price$0.45 / $2.25
- Context262K
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-Coder 30B-A3B Instruct (41). 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 · GLM-4.5V $0.90 · Qwen3-Coder 30B-A3B Instruct $0.90 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Qwen3-Coder 30B-A3B Instruct 262,144 · 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-Coder 30B-A3B Instruct: Text
- Self-hostingGLM-4.5V and Qwen3-Coder 30B-A3B InstructPublishes downloadable weights
| Measure | Weight | GLM-4.5V | GPT-4.1 mini | Qwen3-Coder 30B-A3B Instruct |
|---|---|---|---|---|
| Price | 50% | 52 | 57 | 52 |
| Inputs & features | 30% | 70 | 70 | 25 |
| Context window | 20% | 12 | 61 | 37 |
| Overall | 100% | 49/100 | 62/100 | 41/100 |
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-Coder 30B-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) | $0.45 |
| Output | $1.80 | $1.60 (best) | $2.25 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.90 | $0.70 (best) | $0.90 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.75 / $3.75 |
| Price source | Official Z.AI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 64,000 tokens | 1,047,576 tokens (best) | 262,144 tokens |
| Max output | 16,384 tokens | 32,768 tokens | 65,536 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-coder-30b-a3b-instruct |
| API providers | 11 | 24 (best) | 13 |
| Released | Aug 11, 2025 | Apr 14, 2025 | Apr 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-Coder 30B-A3B Instruct$9.00
Which should you choose?
Which is better: GLM-4.5V, GPT-4.1 mini or Qwen3-Coder 30B-A3B Instruct?
GPT-4.1 mini is the better all-round choice, scoring 62/100 against GLM-4.5V (49) and Qwen3-Coder 30B-A3B Instruct (41). 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-Coder 30B-A3B Instruct?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price); Qwen3-Coder 30B-A3B Instruct costs $0.45 input / $2.25 output per million tokens (official Alibaba 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 $0.90 for GLM-4.5V (1.3× as much) and $0.90 for Qwen3-Coder 30B-A3B Instruct (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-Coder 30B-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-Coder 30B-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 262,144 for Qwen3-Coder 30B-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-Coder 30B-A3B Instruct up to 65,536 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-Coder 30B-A3B Instruct accepts text. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V and Qwen3-Coder 30B-A3B Instruct publishes its weights and can be self-hosted; GPT-4.1 mini is proprietary.
Which is newer?
GLM-4.5V is the newest, released Aug 11, 2025. GPT-4.1 mini came out Apr 14, 2025; Qwen3-Coder 30B-A3B Instruct came out Apr 2025. Knowledge cutoff: GLM-4.5V Apr 2025, GPT-4.1 mini Apr 2024, Qwen3-Coder 30B-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.
