Qwen2.5 7B Instruct vs Gemma 2 27B vs Llama-3.1-8B-Instruct
Too close to call on our weighted score (Qwen2.5 7B Instruct 50, Llama-3.1-8B-Instruct 49, Gemma 2 27B 35). The right pick depends on what you value most.
Alibaba (Qwen)Qwen2.5 7B Instruct
50/100- ECI118.5
- Price$0.05 / $0.10
- Context131K
GoogleGemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
MetaLlama-3.1-8B-Instruct
49/100- ECI116.4
- Price$0.06 / $0.08
- Context128K
Too close to call
It is close. Our weighted score puts them within 1 points (Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100, Gemma 2 27B 35/100), so choose by what matters most for your work: Gemma 2 27B for raw capability, Qwen2.5 7B Instruct on price and Qwen2.5 7B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 2 27BCapabilities Index (ECI): Gemma 2 27B 122.1 · Qwen2.5 7B Instruct 118.5 · Llama-3.1-8B-Instruct 116.4
- Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Llama-3.1-8B-Instruct $0.065 · Gemma 2 27B $0.65 per 1M tokens (3:1 blend)
- Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 · Gemma 2 27B 8,192 tokens
- Widest inputsSame inputsQwen2.5 7B Instruct: Text · Gemma 2 27B: Text · Llama-3.1-8B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen2.5 7B Instruct | Gemma 2 27B | Llama-3.1-8B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 42 | 35 |
| Price | 25% | 100 | 56 | 100 |
| Inputs & features | 15% | 25 | 0 | 25 |
| Context window | 10% | 25 | 0 | 24 |
| Overall | 100% | 50/100 | 35/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen2.5 7B InstructAlibaba (Qwen) | Gemma 2 27BGoogle | Llama-3.1-8B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 | 122.1 (best) | 116.4 |
| ECI rank | #159 of 165 | #152 of 165 (best) | #162 of 165 |
| GPQA DiamondGraduate-level science questions | 35.5% | 36.5% (best) | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.5% (best) | 1.4% | 1.7% |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.65 | $0.06 |
| Output | $0.10 | $0.65 | $0.08 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.063 (best) | $0.65 | $0.065 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 3 providers | Median of 17 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 8,192 tokens | 128,000 tokens |
| Max output | 8,192 tokens (best) | 2,048 tokens | 4,096 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 | No | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Open |
| API model ID | — | — | — |
| API providers | 4 | 3 | 18 (best) |
| Released | Sep 19, 2024 | Jul 13, 2024 | Jul 23, 2024 |
| Knowledge cutoff | — | Jun 30, 2024 | 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
- Gemma 2 27B$7.80
- Llama-3.1-8B-Instruct$0.76
Which should you choose?
Which is better: Qwen2.5 7B Instruct, Gemma 2 27B or Llama-3.1-8B-Instruct?
It is close. Our weighted score puts them within 1 points (Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100, Gemma 2 27B 35/100), so choose by what matters most for your work: Gemma 2 27B for raw capability, Qwen2.5 7B Instruct on price and Qwen2.5 7B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen2.5 7B Instruct, Gemma 2 27B 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); Gemma 2 27B costs $0.65 input / $0.65 output per million tokens (median across 3 API providers). 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 $0.65 for Gemma 2 27B (10× as much).
Which scores higher on benchmarks?
Gemma 2 27B scores higher on the Capabilities Index (ECI): Gemma 2 27B 122.1 (#152 of 165), Qwen2.5 7B Instruct 118.5 (#159 of 165) and Llama-3.1-8B-Instruct 116.4 (#162 of 165). The confidence ranges of the top two overlap (115.8–124.1 vs 110.6–121.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 2 27B 36.5%, Qwen2.5 7B Instruct 35.5%, Llama-3.1-8B-Instruct 27.0%; OTIS Mock AIME 2024–2025 — Qwen2.5 7B Instruct 2.5%, Llama-3.1-8B-Instruct 1.7%, Gemma 2 27B 1.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 7B Instruct, Gemma 2 27B and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Gemma 2 27B leads, which tends to carry over to coding, but test on your own codebase. Note that Gemma 2 27B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen2.5 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama-3.1-8B-Instruct and 8,192 for Gemma 2 27B. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Gemma 2 27B up to 2,048, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5 7B Instruct accepts text; Gemma 2 27B accepts text; Llama-3.1-8B-Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Qwen2.5 7B Instruct is the newest, released Sep 19, 2024. Llama-3.1-8B-Instruct came out Jul 23, 2024; Gemma 2 27B came out Jul 13, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, 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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