GLM-4.5-Air vs Llama 3.3 Nemotron Super 49B v1.5 vs Solar Pro 2
Too close to call on our weighted score (Solar Pro 2 51, Llama 3.3 Nemotron Super 49B v1.5 48, GLM-4.5-Air 48). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5-Air
48/100- ECI—
- Price$0.20 / $1.10
- Context131K
NVIDIALlama 3.3 Nemotron Super 49B v1.5
48/100- ECI—
- Price$0.40 / $0.40
- Context131K
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
Too close to call
It is close. Our weighted score puts them within 2 points (Solar Pro 2 51/100, Llama 3.3 Nemotron Super 49B v1.5 48/100, GLM-4.5-Air 48/100), so choose by what matters most for your work: Solar Pro 2 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 priceSolar Pro 2Solar Pro 2 $0.25 · Llama 3.3 Nemotron Super 49B v1.5 $0.40 · GLM-4.5-Air $0.425 per 1M tokens (3:1 blend)
- Longest contextGLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5GLM-4.5-Air 131,072 · Llama 3.3 Nemotron Super 49B v1.5 131,072 · Solar Pro 2 65,536 tokens
- Widest inputsSame inputsGLM-4.5-Air: Text · Llama 3.3 Nemotron Super 49B v1.5: Text · Solar Pro 2: Text
- Self-hostingGLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5Publishes downloadable weights
| Measure | Weight | GLM-4.5-Air | Llama 3.3 Nemotron Super 49B v1.5 | Solar Pro 2 |
|---|---|---|---|---|
| Price | 50% | 65 | 66 | 75 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 25 | 25 | 12 |
| Overall | 100% | 48/100 | 48/100 | 51/100 |
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) | Llama 3.3 Nemotron Super 49B v1.5NVIDIA | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 (best) | $0.40 | $0.25 |
| Output | $1.10 | $0.40 | $0.25 (best) |
| Cached input | $0.03 | — | — |
| Blended (3:1) | $0.425 | $0.40 | $0.25 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 1 providers | Official Upstage API |
| Limits | |||
| Context window | 131,072 tokens (best) | 131,072 tokens (best) | 65,536 tokens |
| Max output | 98,304 tokens | 131,072 tokens (best) | 8,192 tokens |
| 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 | Yes | Yesminimal · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.5-air | — | solar-pro2 |
| API providers | 19 (best) | 1 | 2 |
| Released | Jul 28, 2025 | Jul 25, 2025 | May 20, 2025 |
| Knowledge cutoff | Apr 2025 | — | Mar 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
- Llama 3.3 Nemotron Super 49B v1.5$4.80
- Solar Pro 2$3.00
Which should you choose?
Which is better: GLM-4.5-Air, Llama 3.3 Nemotron Super 49B v1.5 or Solar Pro 2?
It is close. Our weighted score puts them within 2 points (Solar Pro 2 51/100, Llama 3.3 Nemotron Super 49B v1.5 48/100, GLM-4.5-Air 48/100), so choose by what matters most for your work: Solar Pro 2 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-Air, Llama 3.3 Nemotron Super 49B v1.5 or Solar Pro 2?
Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage API price). Llama 3.3 Nemotron Super 49B v1.5 costs $0.40 input / $0.40 output per million tokens (median across 1 API provider); 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 $0.25 per million tokens for Solar Pro 2 versus $0.40 for Llama 3.3 Nemotron Super 49B v1.5 (1.6× as much) and $0.425 for GLM-4.5-Air (1.7× 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, Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet and Solar Pro 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Air, Llama 3.3 Nemotron Super 49B v1.5 and Solar Pro 2 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-Air and Llama 3.3 Nemotron Super 49B v1.5 have the largest context windows (131,072 and 131,072 tokens), against 65,536 for Solar Pro 2. Maximum output per response: GLM-4.5-Air up to 98,304, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text; Solar Pro 2 accepts text. They handle the same number of input types.
Are any of these open source?
GLM-4.5-Air and Llama 3.3 Nemotron Super 49B v1.5 publishes its weights and can be self-hosted; Solar Pro 2 is proprietary.
Which is newer?
GLM-4.5-Air is the newest, released Jul 28, 2025. Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, Solar Pro 2 Mar 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 Nov 2, 2026.
Related comparisons
- GLM-4.5-Air vs Codestral 25.08Mistral AI
- GLM-4.5-Air vs Qwen3 Omni 30B A3B ThinkingAlibaba (Qwen)
- GLM-4.5-Air vs ERNIE 4.5 300B A47BBaidu
- Llama 3.3 Nemotron Super 49B v1.5 vs Codestral 25.08Mistral AI
- Llama 3.3 Nemotron Super 49B v1.5 vs Gemma-SEA-LION-v4-27B-ITAI Singapore
- Llama 3.3 Nemotron Super 49B v1.5 vs Qwen3 Omni 30B A3B ThinkingAlibaba (Qwen)
