GLM-4.6V-Flash vs Grok 4.1 Fast (Reasoning) vs Ministral 3 14B
Grok 4.1 Fast (Reasoning) comes out ahead, 74 to 65 and 63 on our weighted score, though GLM-4.6V-Flash is 5% cheaper per token.
Z.ai (Zhipu)GLM-4.6V-Flash
65/100- ECI—
- Price$0.161 / $0.559
- Context128K
- Our pick
xAIGrok 4.1 Fast (Reasoning)
74/100- ECI—
- Price$0.20 / $0.50
- Context2M
Mistral AIMinistral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
Grok 4.1 Fast (Reasoning) is our pick
Grok 4.1 Fast (Reasoning) is the better all-round choice, scoring 74/100 against GLM-4.6V-Flash (65) and Ministral 3 14B (63). It leads on 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 priceGLM-4.6V-FlashGLM-4.6V-Flash $0.261 · Grok 4.1 Fast (Reasoning) $0.275 · Ministral 3 14B $0.282 per 1M tokens (3:1 blend)
- Longest contextGrok 4.1 Fast (Reasoning)Grok 4.1 Fast (Reasoning) 2,000,000 · Ministral 3 14B 262,144 · GLM-4.6V-Flash 128,000 tokens
- Widest inputsGLM-4.6V-FlashGLM-4.6V-Flash: Text, Images, Video · Grok 4.1 Fast (Reasoning): Text, Images · 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 | Grok 4.1 Fast (Reasoning) | Ministral 3 14B |
|---|---|---|---|---|
| Price | 50% | 78 | 76 | 76 |
| Inputs & features | 30% | 70 | 70 | 60 |
| Context window | 20% | 24 | 72 | 37 |
| Overall | 100% | 65/100 | 74/100 | 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) | Grok 4.1 Fast (Reasoning)xAI | Ministral 3 14BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.161 (best) | $0.20 | $0.268 |
| Output | $0.559 | $0.50 | $0.325 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.261 (best) | $0.275 | $0.282 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Median of 2 providers |
| Limits | |||
| Context window | 128,000 tokens | 2,000,000 tokens (best) | 262,144 tokens |
| Max output | 32,768 tokens | 30,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | OpenApache 2.0 |
| API model ID | glm-4.6v-flash | — | — |
| API providers | 6 (best) | 2 | 2 |
| Released | Dec 8, 2025 | Nov 19, 2025 | Dec 2, 2025 |
| Knowledge cutoff | — | — | — |
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
- Grok 4.1 Fast (Reasoning)$3.00
- Ministral 3 14B$3.33
Which should you choose?
Which is better: GLM-4.6V-Flash, Grok 4.1 Fast (Reasoning) or Ministral 3 14B?
Grok 4.1 Fast (Reasoning) is the better all-round choice, scoring 74/100 against GLM-4.6V-Flash (65) and Ministral 3 14B (63). It leads on 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-4.6V-Flash, Grok 4.1 Fast (Reasoning) or Ministral 3 14B?
GLM-4.6V-Flash is cheaper at $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI). Grok 4.1 Fast (Reasoning) costs $0.20 input / $0.50 output per million tokens (median across 2 API providers); 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 $0.261 per million tokens for GLM-4.6V-Flash versus $0.275 for Grok 4.1 Fast (Reasoning) (1.1× 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, Grok 4.1 Fast (Reasoning) 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, Grok 4.1 Fast (Reasoning) 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?
Grok 4.1 Fast (Reasoning) has the largest context window at 2,000,000 tokens, against 262,144 for Ministral 3 14B and 128,000 for GLM-4.6V-Flash. Maximum output per response: GLM-4.6V-Flash up to 32,768, Grok 4.1 Fast (Reasoning) up to 30,000, 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; Grok 4.1 Fast (Reasoning) accepts text and images; 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; Grok 4.1 Fast (Reasoning) is proprietary.
Which is newer?
GLM-4.6V-Flash is the newest, released Dec 8, 2025. Ministral 3 14B came out Dec 2, 2025; Grok 4.1 Fast (Reasoning) came out Nov 19, 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.
