GLM-4.6V-Flash vs Solar Pro 2 vs Ministral 3 14B
Too close to call on our weighted score (GLM-4.6V-Flash 65, Ministral 3 14B 63, Solar Pro 2 52). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.6V-Flash
65/100- ECI—
- Price$0.161 / $0.559
- Context128K
Upstage
Solar Pro 2
52/100- ECI—
- Price$0.25 / $0.25
- Context66K
Mistral AIMinistral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
Too close to call
It is close. Our weighted score puts them within 1 points (GLM-4.6V-Flash 65/100, Ministral 3 14B 63/100, Solar Pro 2 52/100), so choose by what matters most for your work: Solar Pro 2 on price and Ministral 3 14B for long inputs. 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 priceSolar Pro 2Solar Pro 2 $0.25 · GLM-4.6V-Flash $0.261 · Ministral 3 14B $0.282 per 1M tokens (3:1 blend)
- Longest contextMinistral 3 14BMinistral 3 14B 262,144 · GLM-4.6V-Flash 128,000 · Solar Pro 2 65,536 tokens
- Widest inputsGLM-4.6V-FlashGLM-4.6V-Flash: Text, Images, Video · Solar Pro 2: Text · Ministral 3 14B: Text, Images
- Self-hostingGLM-4.6V-Flash and Ministral 3 14BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | GLM-4.6V-Flash | Solar Pro 2 | Ministral 3 14B |
|---|---|---|---|---|
| Price | 50% | 78 | 78 | 76 |
| Inputs & features | 30% | 70 | 35 | 60 |
| Context window | 20% | 24 | 12 | 37 |
| Overall | 100% | 65/100 | 52/100 | 63/100 |
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-4.6V-FlashZ.ai (Zhipu) | Solar Pro 2Upstage | Ministral 3 14BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.161 (best) | $0.25 | $0.268 |
| Output | $0.559 | $0.25 (best) | $0.325 |
| Cached input | — | — | — |
| Blended (3:1) | $0.261 | $0.25 (best) | $0.282 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Upstage API | Median of 2 providers |
| Limits | |||
| Context window | 128,000 tokens | 65,536 tokens | 262,144 tokens (best) |
| Max output | 32,768 tokens | 8,192 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yesminimal · high | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | OpenApache 2.0 |
| API model ID | glm-4.6v-flash | solar-pro2 | — |
| API providers | 6 (best) | 2 | 2 |
| Released | Dec 8, 2025 | May 20, 2025 | Dec 2, 2025 |
| Knowledge cutoff | — | Mar 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-4.6V-Flash$2.73
- Solar Pro 2$3.00
- Ministral 3 14B$3.33
Which should you choose?
Which is better: GLM-4.6V-Flash, Solar Pro 2 or Ministral 3 14B?
It is close. Our weighted score puts them within 1 points (GLM-4.6V-Flash 65/100, Ministral 3 14B 63/100, Solar Pro 2 52/100), so choose by what matters most for your work: Solar Pro 2 on price and Ministral 3 14B for long inputs. 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-4.6V-Flash, Solar Pro 2 or Ministral 3 14B?
Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage API price). GLM-4.6V-Flash costs $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI); Ministral 3 14B costs $0.268 input / $0.325 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.25 per million tokens for Solar Pro 2 versus $0.261 for GLM-4.6V-Flash (1× as much) and $0.282 for Ministral 3 14B (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.6V-Flash has not been scored yet, Solar Pro 2 has not been scored yet and Ministral 3 14B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6V-Flash, Solar Pro 2 and Ministral 3 14B 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?
Ministral 3 14B has the largest context window at 262,144 tokens, against 128,000 for GLM-4.6V-Flash and 65,536 for Solar Pro 2. Maximum output per response: GLM-4.6V-Flash up to 32,768, Solar Pro 2 up to 8,192, Ministral 3 14B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6V-Flash accepts text, images and video; Solar Pro 2 accepts text; Ministral 3 14B accepts text and images. GLM-4.6V-Flash handles the widest range of inputs.
Are any of these open source?
GLM-4.6V-Flash and Ministral 3 14B publishes its weights (Apache 2.0) and can be self-hosted; Solar Pro 2 is proprietary.
Which is newer?
GLM-4.6V-Flash is the newest, released Dec 8, 2025. Ministral 3 14B came out Dec 2, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: Solar Pro 2 Mar 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.
