GLM-4.5-Air vs Nemotron Nano 9B v2 vs Seed 1.6 Vision
Too close to call on our weighted score (Nemotron Nano 9B v2 64, Seed 1.6 Vision 63, GLM-4.5-Air 49). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5-Air
49/100- ECI—
- Price$0.20 / $1.10
- Context131K
NVIDIANemotron Nano 9B v2
64/100- ECI—
- Price$0.06 / $0.23
- Context131K
ByteDance SeedSeed 1.6 Vision
63/100- ECI—
- Price$0.119 / $1.19
- Context256K
Too close to call
It is close. Our weighted score puts them within a point (Nemotron Nano 9B v2 64/100, Seed 1.6 Vision 63/100, GLM-4.5-Air 49/100), so choose by what matters most for your work: Nemotron Nano 9B v2 on price and Seed 1.6 Vision 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 priceNemotron Nano 9B v2Nemotron Nano 9B v2 $0.102 · Seed 1.6 Vision $0.386 · GLM-4.5-Air $0.425 per 1M tokens (3:1 blend)
- Longest contextSeed 1.6 VisionSeed 1.6 Vision 256,000 · GLM-4.5-Air 131,072 · Nemotron Nano 9B v2 131,072 tokens
- Widest inputsSeed 1.6 VisionGLM-4.5-Air: Text · Nemotron Nano 9B v2: Text · Seed 1.6 Vision: Text, Images
- Self-hostingGLM-4.5-Air and Nemotron Nano 9B v2Publishes downloadable weights
| Measure | Weight | GLM-4.5-Air | Nemotron Nano 9B v2 | Seed 1.6 Vision |
|---|---|---|---|---|
| Price | 50% | 68 | 97 | 69 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 24 | 24 | 36 |
| Overall | 100% | 49/100 | 64/100 | 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-4.5-AirZ.ai (Zhipu) | Nemotron Nano 9B v2NVIDIA | Seed 1.6 VisionByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.06 (best) | $0.119 |
| Output | $1.10 | $0.23 (best) | $1.19 |
| Cached input | $0.03 | — | $0.024 (best) |
| Blended (3:1) | $0.425 | $0.102 (best) | $0.386 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.178 / $2.37 |
| Price source | Official Z.AI API | Median of 3 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 256,000 tokens (best) |
| Max output | 98,304 tokens | 131,072 tokens (best) | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.5-air | nvidia/nvidia-nemotron-nano-9b-v2 | doubao-seed-1-6-vision-250815 |
| API providers | 13 (best) | 4 | 2 |
| Released | Jul 28, 2025 | Aug 18, 2025 | Aug 15, 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-Air$4.20
- Nemotron Nano 9B v2$1.06
- Seed 1.6 Vision$3.56
Which should you choose?
Which is better: GLM-4.5-Air, Nemotron Nano 9B v2 or Seed 1.6 Vision?
It is close. Our weighted score puts them within a point (Nemotron Nano 9B v2 64/100, Seed 1.6 Vision 63/100, GLM-4.5-Air 49/100), so choose by what matters most for your work: Nemotron Nano 9B v2 on price and Seed 1.6 Vision 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-4.5-Air, Nemotron Nano 9B v2 or Seed 1.6 Vision?
Nemotron Nano 9B v2 is cheaper at $0.06 input / $0.23 output per million tokens (median across 3 API providers; free on Nvidia). Seed 1.6 Vision costs $0.119 input / $1.19 output per million tokens (official Volcengine Ark API price); GLM-4.5-Air costs $0.20 input / $1.10 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.102 per million tokens for Nemotron Nano 9B v2 versus $0.386 for Seed 1.6 Vision (3.8× as much) and $0.425 for GLM-4.5-Air (4.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Air has not been scored yet, Nemotron Nano 9B v2 has not been scored yet and Seed 1.6 Vision has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Air, Nemotron Nano 9B v2 and Seed 1.6 Vision 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?
Seed 1.6 Vision has the largest context window at 256,000 tokens, against 131,072 for GLM-4.5-Air and 131,072 for Nemotron Nano 9B v2. Maximum output per response: GLM-4.5-Air up to 98,304, Nemotron Nano 9B v2 up to 131,072, Seed 1.6 Vision up to 32,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; Nemotron Nano 9B v2 accepts text; Seed 1.6 Vision accepts text and images. Seed 1.6 Vision handles the widest range of inputs.
Are any of these open source?
GLM-4.5-Air and Nemotron Nano 9B v2 publishes its weights and can be self-hosted; Seed 1.6 Vision is proprietary.
Which is newer?
Nemotron Nano 9B v2 is the newest, released Aug 18, 2025. Seed 1.6 Vision came out Aug 15, 2025; GLM-4.5-Air came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Air 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.
