GLM-4.5-Flash vs Nova 2 Pro
Nova 2 Pro comes out ahead, 86 to 65 on our weighted score.
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
- Our pick
AmazonNova 2 Pro
86/100- ECI—
- PriceFree / Free
- Context1M
Add a model
Make it a three-way comparison.
Nova 2 Pro is our pick
Nova 2 Pro is the better all-round choice, scoring 86/100 against GLM-4.5-Flash (65). It leads on inputs & features and 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 priceSame priceGLM-4.5-Flash Free · Nova 2 Pro Free per 1M tokens (3:1 blend)
- Longest contextNova 2 ProNova 2 Pro 1,000,000 · GLM-4.5-Flash 131,072 tokens
- Widest inputsNova 2 ProGLM-4.5-Flash: Text · Nova 2 Pro: Text, Images, PDFs, Video
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GLM-4.5-Flash | Nova 2 Pro |
|---|---|---|---|
| Price | 50% | 100 | 100 |
| Inputs & features | 30% | 35 | 80 |
| Context window | 20% | 24 | 60 |
| Overall | 100% | 65/100 | 86/100 |
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-4.5-FlashZ.ai (Zhipu) | Nova 2 ProAmazon |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | Free | Free |
| Output | Free | Free |
| Cached input | — | — |
| Blended (3:1) | Free | Free |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Nova API |
| Limits | ||
| Context window | 131,072 tokens | 1,000,000 tokens (best) |
| Max output | 98,304 tokens (best) | 64,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | glm-4.5-flash | nova-2-pro-v1 |
| API providers | 4 (best) | 1 |
| Released | Jul 28, 2025 | Dec 3, 2025 |
| 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.
- GLM-4.5-FlashFree
- Nova 2 ProFree
Which should you choose?
Which is better: GLM-4.5-Flash or Nova 2 Pro?
Nova 2 Pro is the better all-round choice, scoring 86/100 against GLM-4.5-Flash (65). It leads on inputs & features and 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-4.5-Flash or Nova 2 Pro?
GLM-4.5-Flash and Nova 2 Pro cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.5-Flash has not been scored yet and Nova 2 Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Flash and Nova 2 Pro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Nova 2 Pro has the largest context window at 1,000,000 tokens, against 131,072 for GLM-4.5-Flash. Maximum output per response: GLM-4.5-Flash up to 98,304, Nova 2 Pro up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Nova 2 Pro accepts text, images, PDFs and video. Nova 2 Pro handles the widest range of inputs.
Are any of these open source?
No. GLM-4.5-Flash and Nova 2 Pro are proprietary and only available through APIs and apps.
Which is newer?
Nova 2 Pro is the newest, released Dec 3, 2025. GLM-4.5-Flash came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Flash 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.
