GLM-4.7-FlashX vs Nova 2 Lite vs Step 3.5 Flash
Too close to call on our weighted score (Step 3.5 Flash 62, Nova 2 Lite 62, GLM-4.7-FlashX 61). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
AmazonNova 2 Lite
62/100- ECI—
- Price$0.33 / $2.75
- Context1M
StepFunStep 3.5 Flash
62/100- ECI—
- Price$0.10 / $0.30
- Context256K
Too close to call
It is close. Our weighted score puts them within a point (Step 3.5 Flash 62/100, Nova 2 Lite 62/100, GLM-4.7-FlashX 61/100), so choose by what matters most for your work: Step 3.5 Flash on price and Nova 2 Lite 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 · Nova 2 Lite $0.935 per 1M tokens (3:1 blend)
- Longest contextNova 2 LiteNova 2 Lite 1,000,000 · Step 3.5 Flash 256,000 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsNova 2 LiteGLM-4.7-FlashX: Text · Nova 2 Lite: Text, Images, PDFs, Video · Step 3.5 Flash: Text
- Self-hostingGLM-4.7-FlashX and Step 3.5 FlashPublishes downloadable weights
| Measure | Weight | GLM-4.7-FlashX | Nova 2 Lite | Step 3.5 Flash |
|---|---|---|---|---|
| Price | 50% | 89 | 51 | 89 |
| Inputs & features | 30% | 35 | 80 | 35 |
| Context window | 20% | 32 | 60 | 36 |
| Overall | 100% | 61/100 | 62/100 | 62/100 |
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) | Nova 2 LiteAmazon | Step 3.5 FlashStepFun |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.07 (best) | $0.33 | $0.10 |
| Output | $0.40 | $2.75 | $0.30 (best) |
| Cached input | $0.01 (best) | $0.083 | $0.02 |
| Blended (3:1) | $0.152 | $0.935 | $0.15 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Amazon Bedrock API | Official StepFun (Global) API |
| Limits | |||
| Context window | 200,000 tokens | 1,000,000 tokens (best) | 256,000 tokens |
| Max output | 131,072 tokens | 65,536 tokens | 256,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yeslow · medium · high | Yeslow · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.7-flashx | amazon.nova-2-lite-v1:0 | step-3.5-flash |
| API providers | 8 (best) | 2 | 8 (best) |
| Released | Jan 19, 2026 | Dec 2, 2025 | Jan 29, 2026 |
| Knowledge cutoff | Apr 2025 | Oct 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
- Nova 2 Lite$8.80
- Step 3.5 Flash$1.60
Which should you choose?
Which is better: GLM-4.7-FlashX, Nova 2 Lite or Step 3.5 Flash?
It is close. Our weighted score puts them within a point (Step 3.5 Flash 62/100, Nova 2 Lite 62/100, GLM-4.7-FlashX 61/100), so choose by what matters most for your work: Step 3.5 Flash on price and Nova 2 Lite 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-4.7-FlashX, Nova 2 Lite or Step 3.5 Flash?
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); Nova 2 Lite costs $0.33 input / $2.75 output per million tokens (official Amazon Bedrock API price). 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 $0.935 for Nova 2 Lite (6.2× 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, Nova 2 Lite has not been scored yet and Step 3.5 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-FlashX, Nova 2 Lite and Step 3.5 Flash 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?
Nova 2 Lite has the largest context window at 1,000,000 tokens, against 256,000 for Step 3.5 Flash and 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-4.7-FlashX up to 131,072, Nova 2 Lite up to 65,536, Step 3.5 Flash up to 256,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-FlashX accepts text; Nova 2 Lite accepts text, images, PDFs and video; Step 3.5 Flash accepts text. Nova 2 Lite handles the widest range of inputs.
Are any of these open source?
GLM-4.7-FlashX and Step 3.5 Flash publishes its weights and can be self-hosted; Nova 2 Lite 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; Nova 2 Lite came out Dec 2, 2025. Knowledge cutoff: GLM-4.7-FlashX Apr 2025, Nova 2 Lite Oct 2025, Step 3.5 Flash 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 Oct 4, 2026.
