Qwen2.5 7B Instruct vs Gemini 2.5 Flash-Lite vs Llama-3.1-8B-Instruct
Gemini 2.5 Flash-Lite comes out ahead, 83 to 62 and 62 on our weighted score, though Qwen2.5 7B Instruct is 2.8× cheaper per token.
Alibaba (Qwen)Qwen2.5 7B Instruct
62/100- ECI118.5
- Price$0.05 / $0.10
- Context131K
- Our pick
GoogleGemini 2.5 Flash-Lite
83/100- ECI—
- Price$0.10 / $0.40
- Context1.05M
MetaLlama-3.1-8B-Instruct
62/100- ECI116.4
- Price$0.06 / $0.08
- Context128K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Qwen2.5 7B Instruct (62) and Llama-3.1-8B-Instruct (62). It leads on inputs & features 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 priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Llama-3.1-8B-Instruct $0.065 · Gemini 2.5 Flash-Lite $0.175 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen2.5 7B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsGemini 2.5 Flash-LiteQwen2.5 7B Instruct: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Llama-3.1-8B-Instruct: Text
- Self-hostingQwen2.5 7B Instruct and Llama-3.1-8B-InstructPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Qwen2.5 7B Instruct | Gemini 2.5 Flash-Lite | Llama-3.1-8B-Instruct |
|---|---|---|---|---|
| Price | 50% | 100 | 82 | 100 |
| Inputs & features | 30% | 25 | 100 | 25 |
| Context window | 20% | 25 | 61 | 24 |
| Overall | 100% | 62/100 | 83/100 | 62/100 |
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 | Qwen2.5 7B InstructAlibaba (Qwen) | Gemini 2.5 Flash-LiteGoogle | Llama-3.1-8B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 (best) | — | 116.4 |
| ECI rank | #159 of 165 (best) | — | #162 of 165 |
| GPQA DiamondGraduate-level science questions | 35.5% (best) | — | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.5% (best) | — | 1.7% |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.10 | $0.06 |
| Output | $0.10 | $0.40 | $0.08 (best) |
| Cached input | — | $0.01 | — |
| Blended (3:1) | $0.063 (best) | $0.175 | $0.065 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Google API | Median of 17 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,048,576 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 65,536 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Open |
| API model ID | — | gemini-2.5-flash-lite | — |
| API providers | 4 | 24 (best) | 18 |
| Released | Sep 19, 2024 | Jun 17, 2025 | Jul 23, 2024 |
| Knowledge cutoff | — | Jan 2025 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen2.5 7B Instruct$0.70
- Gemini 2.5 Flash-Lite$1.80
- Llama-3.1-8B-Instruct$0.76
Which should you choose?
Which is better: Qwen2.5 7B Instruct, Gemini 2.5 Flash-Lite or Llama-3.1-8B-Instruct?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Qwen2.5 7B Instruct (62) and Llama-3.1-8B-Instruct (62). It leads on inputs & features 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, Qwen2.5 7B Instruct, Gemini 2.5 Flash-Lite or Llama-3.1-8B-Instruct?
Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Llama-3.1-8B-Instruct costs $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). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Qwen2.5 7B Instruct versus $0.065 for Llama-3.1-8B-Instruct (1× as much) and $0.175 for Gemini 2.5 Flash-Lite (2.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen2.5 7B Instruct has an ECI of 118.5, Gemini 2.5 Flash-Lite has not been scored yet and Llama-3.1-8B-Instruct has an ECI of 116.4.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 7B Instruct, Gemini 2.5 Flash-Lite and Llama-3.1-8B-Instruct 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 131,072 for Qwen2.5 7B Instruct and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Gemini 2.5 Flash-Lite up to 65,536, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5 7B Instruct accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Llama-3.1-8B-Instruct accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Qwen2.5 7B Instruct and Llama-3.1-8B-Instruct publishes its weights (Apache 2.0) and can be self-hosted; Gemini 2.5 Flash-Lite is proprietary.
Which is newer?
Gemini 2.5 Flash-Lite is the newest, released Jun 17, 2025. Qwen2.5 7B Instruct came out Sep 19, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, Llama-3.1-8B-Instruct Dec 2023.
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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