Llama-3.1-8B-Instruct vs Saba vs Solar Pro 2
Llama-3.1-8B-Instruct comes out ahead, 62 to 51 and 46 on our weighted score, and it is the cheaper option too.
- Our pick
MetaLlama-3.1-8B-Instruct
62/100- ECI116.4
- Price$0.06 / $0.08
- Context128K
Mistral AISaba
46/100- ECI—
- Price$0.20 / $0.60
- Context33K
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
Llama-3.1-8B-Instruct is our pick
Llama-3.1-8B-Instruct is the better all-round choice, scoring 62/100 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-3.1-8B-InstructLlama-3.1-8B-Instruct $0.065 · Solar Pro 2 $0.25 · Saba $0.30 per 1M tokens (3:1 blend)
- Longest contextLlama-3.1-8B-InstructLlama-3.1-8B-Instruct 128,000 · Solar Pro 2 65,536 · Saba 32,768 tokens
- Widest inputsSabaLlama-3.1-8B-Instruct: Text · Saba: Text, PDFs · Solar Pro 2: Text
- Self-hostingLlama-3.1-8B-InstructPublishes downloadable weights
| Measure | Weight | Llama-3.1-8B-Instruct | Saba | Solar Pro 2 |
|---|---|---|---|---|
| Price | 50% | 100 | 72 | 75 |
| Inputs & features | 30% | 25 | 35 | 35 |
| Context window | 20% | 24 | 0 | 12 |
| Overall | 100% | 62/100 | 46/100 | 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 | Llama-3.1-8B-InstructMeta | SabaMistral AI | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 116.4 | — | — |
| ECI rank | #162 of 165 | — | — |
| GPQA DiamondGraduate-level science questions | 27.0% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.7% | — | — |
| Price per million tokens | |||
| Input | $0.06 (best) | $0.20 | $0.25 |
| Output | $0.08 (best) | $0.60 | $0.25 |
| Cached input | — | — | — |
| Blended (3:1) | $0.065 (best) | $0.30 | $0.25 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 17 providers | Median of 4 providers | Official Upstage API |
| Limits | |||
| Context window | 128,000 tokens (best) | 32,768 tokens | 65,536 tokens |
| Max output | 4,096 tokens | 26,214 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yesminimal · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | — | solar-pro2 |
| API providers | 18 (best) | 4 | 2 |
| Released | Jul 23, 2024 | Feb 17, 2025 | May 20, 2025 |
| Knowledge cutoff | Dec 2023 | 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.
- Llama-3.1-8B-Instruct$0.76
- Saba$3.20
- Solar Pro 2$3.00
Which should you choose?
Which is better: Llama-3.1-8B-Instruct, Saba or Solar Pro 2?
Llama-3.1-8B-Instruct is the better all-round choice, scoring 62/100 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, Llama-3.1-8B-Instruct, Saba or Solar Pro 2?
Llama-3.1-8B-Instruct is cheaper at $0.06 input / $0.08 output per million tokens (median across 17 API providers). 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 $0.065 per million tokens for Llama-3.1-8B-Instruct versus $0.25 for Solar Pro 2 (3.8× as much) and $0.30 for Saba (4.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.1-8B-Instruct has an ECI of 116.4, Saba 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 Llama-3.1-8B-Instruct, Saba 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-3.1-8B-Instruct has the largest context window at 128,000 tokens, against 65,536 for Solar Pro 2 and 32,768 for Saba. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Saba up to 26,214, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.1-8B-Instruct accepts text; Saba accepts text and PDFs; Solar Pro 2 accepts text. Saba handles the widest range of inputs.
Are any of these open source?
Llama-3.1-8B-Instruct 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. Saba came out Feb 17, 2025; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, 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.
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