GLM-4.7-FlashX vs Ministral 3 8B vs Step 3.5 Flash 2603
Ministral 3 8B comes out ahead, 68 to 63 and 59 on our weighted score.
Z.ai (Zhipu)GLM-4.7-FlashX
59/100- ECI—
- Price$0.07 / $0.40
- Context200K
- Our pick
Mistral AIMinistral 3 8B
68/100- ECI—
- Price$0.15 / $0.15
- Context262K
StepFunStep 3.5 Flash 2603
63/100- ECI—
- Price$0.10 / $0.30
- Context256K
Ministral 3 8B is our pick
Ministral 3 8B is the better all-round choice, scoring 68/100 against Step 3.5 Flash 2603 (63) and GLM-4.7-FlashX (59). It leads 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 priceMinistral 3 8B and Step 3.5 Flash 2603Ministral 3 8B $0.15 · Step 3.5 Flash 2603 $0.15 · GLM-4.7-FlashX $0.152 per 1M tokens (3:1 blend)
- Longest contextMinistral 3 8BMinistral 3 8B 262,144 · Step 3.5 Flash 2603 256,000 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsMinistral 3 8BGLM-4.7-FlashX: Text · Ministral 3 8B: Text, Images · Step 3.5 Flash 2603: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-4.7-FlashX | Ministral 3 8B | Step 3.5 Flash 2603 |
|---|---|---|---|---|
| Price | 50% | 85 | 85 | 85 |
| Inputs & features | 30% | 35 | 60 | 45 |
| Context window | 20% | 32 | 37 | 36 |
| Overall | 100% | 59/100 | 68/100 | 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-4.7-FlashXZ.ai (Zhipu) | Ministral 3 8BMistral AI | Step 3.5 Flash 2603StepFun |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.07 (best) | $0.15 | $0.10 |
| Output | $0.40 | $0.15 (best) | $0.30 |
| Cached input | $0.01 (best) | $0.015 | $0.02 |
| Blended (3:1) | $0.152 | $0.15 (best) | $0.15 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API | Official StepFun (Global) API |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 256,000 tokens |
| Max output | 131,072 tokens | 262,144 tokens (best) | 256,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yeslow · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Open |
| API model ID | glm-4.7-flashx | ministral-8b-2512 | step-3.5-flash-2603 |
| API providers | 10 | 11 (best) | 4 |
| Released | Jan 19, 2026 | Dec 2, 2025 | Apr 2, 2026 |
| Knowledge cutoff | Apr 2025 | — | Jan 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-4.7-FlashX$1.50
- Ministral 3 8B$1.80
- Step 3.5 Flash 2603$1.60
Which should you choose?
Which is better: GLM-4.7-FlashX, Ministral 3 8B or Step 3.5 Flash 2603?
Ministral 3 8B is the better all-round choice, scoring 68/100 against Step 3.5 Flash 2603 (63) and GLM-4.7-FlashX (59). It leads 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-4.7-FlashX, Ministral 3 8B or Step 3.5 Flash 2603?
Ministral 3 8B is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Step 3.5 Flash 2603 costs $0.10 input / $0.30 output per million tokens (official StepFun (Global) API price); GLM-4.7-FlashX costs $0.07 input / $0.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Ministral 3 8B versus $0.15 for Step 3.5 Flash 2603 (1× as much) and $0.152 for GLM-4.7-FlashX (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.7-FlashX has not been scored yet, Ministral 3 8B has not been scored yet and Step 3.5 Flash 2603 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-FlashX, Ministral 3 8B and Step 3.5 Flash 2603 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 has the largest context window at 262,144 tokens, against 256,000 for Step 3.5 Flash 2603 and 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, Ministral 3 8B up to 262,144, Step 3.5 Flash 2603 up to 256,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; Ministral 3 8B accepts text and images; Step 3.5 Flash 2603 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?
Step 3.5 Flash 2603 is the newest, released Apr 2, 2026. GLM-4.7-FlashX came out Jan 19, 2026; Ministral 3 8B came out Dec 2, 2025. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, Step 3.5 Flash 2603 Jan 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 Nov 2, 2026.
