GLM-4.5-Flash vs Mistral Nemotron vs Nemotron Nano 9B v2
Too close to call on our weighted score (GLM-4.5-Flash 65, Nemotron Nano 9B v2 64, Mistral Nemotron 62). The right pick depends on what you value most.
Z.ai (Zhipu)
GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
NVIDIA
Mistral Nemotron
62/100- ECI—
- PriceFree / Free
- Context128K
NVIDIA
Nemotron Nano 9B v2
64/100- ECI—
- Price$0.06 / $0.23
- Context131K
Too close to call
It is close. Our weighted score puts them within 2 points (GLM-4.5-Flash 65/100, Nemotron Nano 9B v2 64/100, Mistral Nemotron 62/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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 priceGLM-4.5-Flash and Mistral NemotronGLM-4.5-Flash Free · Mistral Nemotron Free · Nemotron Nano 9B v2 $0.102 per 1M tokens (3:1 blend)
- Longest contextGLM-4.5-Flash and Nemotron Nano 9B v2GLM-4.5-Flash 131,072 · Nemotron Nano 9B v2 131,072 · Mistral Nemotron 128,000 tokens
- Widest inputsSame inputsGLM-4.5-Flash: Text · Mistral Nemotron: Text · Nemotron Nano 9B v2: Text
- Self-hostingMistral Nemotron and Nemotron Nano 9B v2Publishes downloadable weights
| Measure | Weight | GLM-4.5-Flash | Mistral Nemotron | Nemotron Nano 9B v2 |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 97 |
| Inputs & features | 30% | 35 | 25 | 35 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 65/100 | 62/100 | 64/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free (best) | Free (best) | $0.06 |
| Output | Free (best) | Free (best) | $0.23 |
| Cached input | — | — | — |
| Blended (3:1) | Free (best) | Free (best) | $0.102 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Nvidia API | Median of 3 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 98,304 tokens | 8,192 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | glm-4.5-flash | mistralai/mistral-nemotron | nvidia/nvidia-nemotron-nano-9b-v2 |
| API providers | 4 (best) | 1 | 4 (best) |
| Released | Jul 28, 2025 | Jun 11, 2025 | Aug 18, 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
Mistral NemotronFree
Nemotron Nano 9B v2$1.06
Which should you choose?
Which is better: GLM-4.5-Flash, Mistral Nemotron or Nemotron Nano 9B v2?
It is close. Our weighted score puts them within 2 points (GLM-4.5-Flash 65/100, Nemotron Nano 9B v2 64/100, Mistral Nemotron 62/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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, Mistral Nemotron or Nemotron Nano 9B v2?
GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). Mistral Nemotron costs Free input / Free output per million tokens (official Nvidia API price); Nemotron Nano 9B v2 costs $0.06 input / $0.23 output per million tokens (median across 3 API providers; free on Nvidia). GLM-4.5-Flash is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Flash has not been scored yet, Mistral Nemotron has not been scored yet and Nemotron Nano 9B v2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Flash, Mistral Nemotron and Nemotron Nano 9B v2 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?
GLM-4.5-Flash and Nemotron Nano 9B v2 have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Mistral Nemotron. Maximum output per response: GLM-4.5-Flash up to 98,304, Mistral Nemotron up to 8,192, Nemotron Nano 9B v2 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Mistral Nemotron accepts text; Nemotron Nano 9B v2 accepts text. They handle the same number of input types.
Are any of these open source?
Mistral Nemotron and Nemotron Nano 9B v2 publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
Nemotron Nano 9B v2 is the newest, released Aug 18, 2025. GLM-4.5-Flash came out Jul 28, 2025; Mistral Nemotron came out Jun 11, 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.