Step 3.5 Flash vs GPT-5.1 Codex mini vs GLM-4.7-FlashX
Too close to call on our weighted score (Step 3.5 Flash 62, GLM-4.7-FlashX 61, GPT-5.1 Codex mini 59). The right pick depends on what you value most.
StepFunStep 3.5 Flash
62/100- ECI—
- Price$0.10 / $0.30
- Context256K
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
Too close to call
It is close. Our weighted score puts them within 1 points (Step 3.5 Flash 62/100, GLM-4.7-FlashX 61/100, GPT-5.1 Codex mini 59/100), so choose by what matters most for your work: Step 3.5 Flash on price and GPT-5.1 Codex mini 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 priceStep 3.5 FlashStep 3.5 Flash $0.15 · GLM-4.7-FlashX $0.152 · GPT-5.1 Codex mini $0.688 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Step 3.5 Flash 256,000 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsGPT-5.1 Codex miniStep 3.5 Flash: Text · GPT-5.1 Codex mini: Text, Images · GLM-4.7-FlashX: Text
- Self-hostingStep 3.5 Flash and GLM-4.7-FlashXPublishes downloadable weights
| Measure | Weight | Step 3.5 Flash | GPT-5.1 Codex mini | GLM-4.7-FlashX |
|---|---|---|---|---|
| Price | 50% | 89 | 58 | 89 |
| Inputs & features | 30% | 35 | 70 | 35 |
| Context window | 20% | 36 | 44 | 32 |
| Overall | 100% | 62/100 | 59/100 | 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 | Step 3.5 FlashStepFun | GPT-5.1 Codex miniOpenAI | GLM-4.7-FlashXZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | $0.25 | $0.07 (best) |
| Output | $0.30 (best) | $2.00 | $0.40 |
| Cached input | $0.02 | — | $0.01 (best) |
| Blended (3:1) | $0.15 (best) | $0.688 | $0.152 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official StepFun (Global) API | Median of 10 providers | Official Z.AI API |
| Limits | |||
| Context window | 256,000 tokens | 400,000 tokens (best) | 200,000 tokens |
| Max output | 256,000 tokens (best) | 128,000 tokens | 131,072 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 | Yeslow · high | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | step-3.5-flash | — | glm-4.7-flashx |
| API providers | 8 | 10 (best) | 8 |
| Released | Jan 29, 2026 | Nov 13, 2025 | Jan 19, 2026 |
| Knowledge cutoff | Jan 2025 | Sep 30, 2024 | 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.
- Step 3.5 Flash$1.60
- GPT-5.1 Codex mini$6.50
- GLM-4.7-FlashX$1.50
Which should you choose?
Which is better: Step 3.5 Flash, GPT-5.1 Codex mini or GLM-4.7-FlashX?
It is close. Our weighted score puts them within 1 points (Step 3.5 Flash 62/100, GLM-4.7-FlashX 61/100, GPT-5.1 Codex mini 59/100), so choose by what matters most for your work: Step 3.5 Flash on price and GPT-5.1 Codex mini 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, Step 3.5 Flash, GPT-5.1 Codex mini or GLM-4.7-FlashX?
Step 3.5 Flash is cheaper at $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); GPT-5.1 Codex mini costs $0.25 input / $2.00 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Step 3.5 Flash versus $0.152 for GLM-4.7-FlashX (1× as much) and $0.688 for GPT-5.1 Codex mini (4.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Step 3.5 Flash has not been scored yet, GPT-5.1 Codex mini 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 Step 3.5 Flash, GPT-5.1 Codex mini 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?
GPT-5.1 Codex mini has the largest context window at 400,000 tokens, against 256,000 for Step 3.5 Flash and 200,000 for GLM-4.7-FlashX. Maximum output per response: Step 3.5 Flash up to 256,000, GPT-5.1 Codex mini up to 128,000, GLM-4.7-FlashX up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Step 3.5 Flash accepts text; GPT-5.1 Codex mini accepts text and images; GLM-4.7-FlashX accepts text. GPT-5.1 Codex mini handles the widest range of inputs.
Are any of these open source?
Step 3.5 Flash and GLM-4.7-FlashX publishes its weights and can be self-hosted; GPT-5.1 Codex mini is proprietary.
Which is newer?
Step 3.5 Flash is the newest, released Jan 29, 2026. GLM-4.7-FlashX came out Jan 19, 2026; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: Step 3.5 Flash Jan 2025, GPT-5.1 Codex mini Sep 30, 2024, 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.
