Saba vs Llama 3.3 Nemotron Super 49B v1 vs Solar Pro 2
Llama 3.3 Nemotron Super 49B v1 comes out ahead, 58 to 51 and 46 on our weighted score, and it is the cheaper option too.
Mistral AISaba
46/100- ECI—
- Price$0.20 / $0.60
- Context33K
- Our pick
NVIDIALlama 3.3 Nemotron Super 49B v1
58/100- ECI—
- Price$0.15 / $0.15
- Context131K
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
Llama 3.3 Nemotron Super 49B v1 is our pick
Llama 3.3 Nemotron Super 49B v1 is the better all-round choice, scoring 58/100 against Solar Pro 2 (51) and Saba (46). It leads on price 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 priceLlama 3.3 Nemotron Super 49B v1Llama 3.3 Nemotron Super 49B v1 $0.15 · Solar Pro 2 $0.25 · Saba $0.30 per 1M tokens (3:1 blend)
- Longest contextLlama 3.3 Nemotron Super 49B v1Llama 3.3 Nemotron Super 49B v1 131,072 · Solar Pro 2 65,536 · Saba 32,768 tokens
- Widest inputsSabaSaba: Text, PDFs · Llama 3.3 Nemotron Super 49B v1: Text · Solar Pro 2: Text
- Self-hostingLlama 3.3 Nemotron Super 49B v1Publishes downloadable weights
| Measure | Weight | Saba | Llama 3.3 Nemotron Super 49B v1 | Solar Pro 2 |
|---|---|---|---|---|
| Price | 50% | 72 | 85 | 75 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 0 | 25 | 12 |
| Overall | 100% | 46/100 | 58/100 | 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 | SabaMistral AI | Llama 3.3 Nemotron Super 49B v1NVIDIA | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.15 (best) | $0.25 |
| Output | $0.60 | $0.15 (best) | $0.25 |
| Cached input | — | — | — |
| Blended (3:1) | $0.30 | $0.15 (best) | $0.25 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Median of 1 providers | Official Upstage API |
| Limits | |||
| Context window | 32,768 tokens | 131,072 tokens (best) | 65,536 tokens |
| Max output | 26,214 tokens | 131,072 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yesminimal · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | — | solar-pro2 |
| API providers | 4 (best) | 1 | 2 |
| Released | Feb 17, 2025 | Mar 18, 2025 | May 20, 2025 |
| Knowledge cutoff | Sep 30, 2024 | — | 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.
- Saba$3.20
- Llama 3.3 Nemotron Super 49B v1$1.80
- Solar Pro 2$3.00
Which should you choose?
Which is better: Saba, Llama 3.3 Nemotron Super 49B v1 or Solar Pro 2?
Llama 3.3 Nemotron Super 49B v1 is the better all-round choice, scoring 58/100 against Solar Pro 2 (51) and Saba (46). It leads on price 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, Saba, Llama 3.3 Nemotron Super 49B v1 or Solar Pro 2?
Llama 3.3 Nemotron Super 49B v1 is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). Solar Pro 2 costs $0.25 input / $0.25 output per million tokens (official Upstage API price); Saba costs $0.20 input / $0.60 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Llama 3.3 Nemotron Super 49B v1 versus $0.25 for Solar Pro 2 (1.7× as much) and $0.30 for Saba (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Saba has not been scored yet, Llama 3.3 Nemotron Super 49B v1 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 Saba, Llama 3.3 Nemotron Super 49B v1 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?
Llama 3.3 Nemotron Super 49B v1 has the largest context window at 131,072 tokens, against 65,536 for Solar Pro 2 and 32,768 for Saba. Maximum output per response: Saba up to 26,214, Llama 3.3 Nemotron Super 49B v1 up to 131,072, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Saba accepts text and PDFs; Llama 3.3 Nemotron Super 49B v1 accepts text; Solar Pro 2 accepts text. Saba handles the widest range of inputs.
Are any of these open source?
Llama 3.3 Nemotron Super 49B v1 publishes its weights and can be self-hosted; Saba and Solar Pro 2 is proprietary.
Which is newer?
Solar Pro 2 is the newest, released May 20, 2025. Llama 3.3 Nemotron Super 49B v1 came out Mar 18, 2025; Saba came out Feb 17, 2025. Knowledge cutoff: Saba Sep 30, 2024, 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.
