Solar Pro 2 vs Llama-3.1-8B-Instruct vs Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite comes out ahead, 83 to 62 and 51 on our weighted score, though Llama-3.1-8B-Instruct is 2.7× cheaper per token.
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
MetaLlama-3.1-8B-Instruct
62/100- ECI116.4
- Price$0.06 / $0.08
- Context128K
- Our pick
GoogleGemini 2.5 Flash-Lite
83/100- ECI—
- Price$0.10 / $0.40
- Context1.05M
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Llama-3.1-8B-Instruct (62) and Solar Pro 2 (51). It leads on inputs & features and context window. Llama-3.1-8B-Instruct wins 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 priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.065 · Gemini 2.5 Flash-Lite $0.175 · Solar Pro 2 $0.25 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Llama-3.1-8B-Instruct 128,000 · Solar Pro 2 65,536 tokens
- Widest inputsGemini 2.5 Flash-LiteSolar Pro 2: Text · Llama-3.1-8B-Instruct: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video
- Self-hostingLlama-3.1-8B-InstructPublishes downloadable weights
| Measure | Weight | Solar Pro 2 | Llama-3.1-8B-Instruct | Gemini 2.5 Flash-Lite |
|---|---|---|---|---|
| Price | 50% | 75 | 100 | 82 |
| Inputs & features | 30% | 35 | 25 | 100 |
| Context window | 20% | 12 | 24 | 61 |
| Overall | 100% | 51/100 | 62/100 | 83/100 |
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 | Solar Pro 2Upstage | Llama-3.1-8B-InstructMeta | Gemini 2.5 Flash-LiteGoogle |
|---|---|---|---|
| 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 | $0.25 | $0.06 (best) | $0.10 |
| Output | $0.25 | $0.08 (best) | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.25 | $0.065 (best) | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Upstage API | Median of 17 providers | Official Google API |
| Limits | |||
| Context window | 65,536 tokens | 128,000 tokens | 1,048,576 tokens (best) |
| Max output | 8,192 tokens | 4,096 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yesminimal · high | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | solar-pro2 | — | gemini-2.5-flash-lite |
| API providers | 2 | 18 | 24 (best) |
| Released | May 20, 2025 | Jul 23, 2024 | Jun 17, 2025 |
| Knowledge cutoff | Mar 2025 | Dec 2023 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Solar Pro 2$3.00
- Llama-3.1-8B-Instruct$0.76
- Gemini 2.5 Flash-Lite$1.80
Which should you choose?
Which is better: Solar Pro 2, Llama-3.1-8B-Instruct or Gemini 2.5 Flash-Lite?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Llama-3.1-8B-Instruct (62) and Solar Pro 2 (51). It leads on inputs & features and context window. Llama-3.1-8B-Instruct wins 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, Solar Pro 2, Llama-3.1-8B-Instruct or Gemini 2.5 Flash-Lite?
Llama-3.1-8B-Instruct is cheaper at $0.06 input / $0.08 output per million tokens (median across 17 API providers). Gemini 2.5 Flash-Lite costs $0.10 input / $0.40 output per million tokens (official Google API price); Solar Pro 2 costs $0.25 input / $0.25 output per million tokens (official Upstage API price). 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 $0.175 for Gemini 2.5 Flash-Lite (2.7× as much) and $0.25 for Solar Pro 2 (3.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Solar Pro 2 has not been scored yet, Llama-3.1-8B-Instruct has an ECI of 116.4 and Gemini 2.5 Flash-Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Solar Pro 2, Llama-3.1-8B-Instruct and Gemini 2.5 Flash-Lite 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?
Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 128,000 for Llama-3.1-8B-Instruct and 65,536 for Solar Pro 2. Maximum output per response: Solar Pro 2 up to 8,192, Llama-3.1-8B-Instruct up to 4,096, Gemini 2.5 Flash-Lite up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Solar Pro 2 accepts text; Llama-3.1-8B-Instruct accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video. Gemini 2.5 Flash-Lite 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; Solar Pro 2 and Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Gemini 2.5 Flash-Lite is the newest, released Jun 17, 2025. Solar Pro 2 came out May 20, 2025; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Solar Pro 2 Mar 2025, Llama-3.1-8B-Instruct Dec 2023, Gemini 2.5 Flash-Lite Jan 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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