GLM-5V-Turbo vs GPT-4.1 mini vs QwQ 32B
GPT-4.1 mini comes out ahead, 62 to 49 and 43 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
OpenAIGPT-4.1 mini
62/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Alibaba (Qwen)QwQ 32B
43/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 62/100 against GLM-5V-Turbo (49) and QwQ 32B (43). It leads on context window. GLM-5V-Turbo wins 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 priceGPT-4.1 miniGPT-4.1 mini $0.70 · QwQ 32B $0.745 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · GLM-5V-Turbo 200,000 · QwQ 32B 131,072 tokens
- Widest inputsGLM-5V-TurboGLM-5V-Turbo: Text, Images, PDFs, Video · GPT-4.1 mini: Text, Images, PDFs · QwQ 32B: Text
- Self-hostingQwQ 32BPublishes downloadable weights
| Measure | Weight | GLM-5V-Turbo | GPT-4.1 mini | QwQ 32B |
|---|---|---|---|---|
| Price | 50% | 37 | 57 | 56 |
| Inputs & features | 30% | 80 | 70 | 35 |
| Context window | 20% | 32 | 61 | 24 |
| Overall | 100% | 49/100 | 62/100 | 43/100 |
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-5V-TurboZ.ai (Zhipu) | GPT-4.1 miniOpenAI | QwQ 32BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 135.0 | 137.6 (best) |
| ECI rank | — | #115 of 148 | #109 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 65.9% (best) | 65.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 44.7% | 59.2% (best) |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | $1.20 | $0.40 (best) | $0.66 |
| Output | $4.00 | $1.60 | $1.00 (best) |
| Cached input | $0.24 | $0.10 (best) | — |
| Blended (3:1) | $1.90 | $0.70 (best) | $0.745 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Median of 1 providers |
| Limits | |||
| Context window | 200,000 tokens | 1,047,576 tokens (best) | 131,072 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | Yes | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | glm-5v-turbo | gpt-4.1-mini | — |
| API providers | 14 | 24 (best) | 1 |
| Released | Apr 1, 2026 | Apr 14, 2025 | Mar 5, 2025 |
| Knowledge cutoff | — | Apr 2024 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5V-Turbo$20.00
- GPT-4.1 mini$7.20
- QwQ 32B$8.60
Which should you choose?
Which is better: GLM-5V-Turbo, GPT-4.1 mini or QwQ 32B?
GPT-4.1 mini is the better all-round choice, scoring 62/100 against GLM-5V-Turbo (49) and QwQ 32B (43). It leads on context window. GLM-5V-Turbo wins 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, GLM-5V-Turbo, GPT-4.1 mini or QwQ 32B?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). QwQ 32B costs $0.66 input / $1.00 output per million tokens (median across 1 API provider); GLM-5V-Turbo costs $1.20 input / $4.00 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 $0.745 for QwQ 32B (1.1× as much) and $1.90 for GLM-5V-Turbo (2.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5V-Turbo has not been scored yet, GPT-4.1 mini has an ECI of 135.0 and QwQ 32B has an ECI of 137.6.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5V-Turbo, GPT-4.1 mini and QwQ 32B 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 200,000 for GLM-5V-Turbo and 131,072 for QwQ 32B. Maximum output per response: GLM-5V-Turbo up to 131,072, GPT-4.1 mini up to 32,768, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-5V-Turbo accepts text, images, PDFs and video; GPT-4.1 mini accepts text, images and PDFs; QwQ 32B accepts text. GLM-5V-Turbo handles the widest range of inputs.
Are any of these open source?
QwQ 32B publishes its weights and can be self-hosted; GLM-5V-Turbo and GPT-4.1 mini is proprietary.
Which is newer?
GLM-5V-Turbo is the newest, released Apr 1, 2026. GPT-4.1 mini came out Apr 14, 2025; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: GPT-4.1 mini Apr 2024, QwQ 32B Apr 2024.
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.
