Ministral 3 8B vs Ministral 3 14B vs GLM-4.7-FlashX
Ministral 3 8B comes out ahead, 70 to 63 and 61 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AIMinistral 3 8B
70/100- ECI—
- Price$0.15 / $0.15
- Context262K
- Mistral AI
Ministral 3 14B
63/100- ECI—
- Price$0.268 / $0.325
- Context262K
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
Ministral 3 8B is our pick
Ministral 3 8B is the better all-round choice, scoring 70/100 against Ministral 3 14B (63) and GLM-4.7-FlashX (61). 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 priceMinistral 3 8BMinistral 3 8B $0.15 · GLM-4.7-FlashX $0.152 · Ministral 3 14B $0.282 per 1M tokens (3:1 blend)
- Longest contextMinistral 3 8B and Ministral 3 14BMinistral 3 8B 262,144 · Ministral 3 14B 262,144 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsMinistral 3 8B and Ministral 3 14BMinistral 3 8B: Text, Images · Ministral 3 14B: Text, Images · GLM-4.7-FlashX: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ministral 3 8B | Ministral 3 14B | GLM-4.7-FlashX |
|---|---|---|---|---|
| Price | 50% | 89 | 76 | 89 |
| Inputs & features | 30% | 60 | 60 | 35 |
| Context window | 20% | 37 | 37 | 32 |
| Overall | 100% | 70/100 | 63/100 | 61/100 |
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 | Ministral 3 8BMistral AI | Ministral 3 14BMistral AI | GLM-4.7-FlashXZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.15 | $0.268 | $0.07 (best) |
| Output | $0.15 (best) | $0.325 | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.15 (best) | $0.282 | $0.152 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 2 providers | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 200,000 tokens |
| Max output | 262,144 tokens (best) | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | OpenApache 2.0 | OpenApache 2.0 | Open |
| API model ID | — | — | glm-4.7-flashx |
| API providers | 1 | 2 | 8 (best) |
| Released | Dec 2, 2025 | Dec 2, 2025 | Jan 19, 2026 |
| Knowledge cutoff | — | — | 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.
- Ministral 3 8B$1.80
- Ministral 3 14B$3.33
- GLM-4.7-FlashX$1.50
Which should you choose?
Which is better: Ministral 3 8B, Ministral 3 14B or GLM-4.7-FlashX?
Ministral 3 8B is the better all-round choice, scoring 70/100 against Ministral 3 14B (63) and GLM-4.7-FlashX (61). 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, Ministral 3 8B, Ministral 3 14B or GLM-4.7-FlashX?
Ministral 3 8B is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). GLM-4.7-FlashX costs $0.07 input / $0.40 output per million tokens (official Z.AI API price); 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 $0.15 per million tokens for Ministral 3 8B versus $0.152 for GLM-4.7-FlashX (1× as much) and $0.282 for Ministral 3 14B (1.9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Ministral 3 8B has not been scored yet, Ministral 3 14B has not been scored yet and GLM-4.7-FlashX has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 3 8B, Ministral 3 14B and GLM-4.7-FlashX 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 8B and Ministral 3 14B have the largest context windows (262,144 and 262,144 tokens), against 200,000 for GLM-4.7-FlashX. Maximum output per response: Ministral 3 8B up to 262,144, Ministral 3 14B up to 262,144, GLM-4.7-FlashX up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Ministral 3 8B accepts text and images; Ministral 3 14B accepts text and images; GLM-4.7-FlashX accepts text. Ministral 3 8B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
GLM-4.7-FlashX is the newest, released Jan 19, 2026. Ministral 3 8B came out Dec 2, 2025; Ministral 3 14B came out Dec 2, 2025. Knowledge cutoff: GLM-4.7-FlashX 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.
