Qwen2.5 7B Instruct vs Gemma 3 4B IT vs Llama-3.1-8B-Instruct
Too close to call on our weighted score (Gemma 3 4B IT 52, Qwen2.5 7B Instruct 50, Llama-3.1-8B-Instruct 49). 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 3 4B IT
52/100- ECI115.8
- Price$0.05 / $0.10
- Context131K
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 2 points (Gemma 3 4B IT 52/100, Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100), so choose by what matters most for your work: Qwen2.5 7B Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen2.5 7B InstructCapabilities Index (ECI): Qwen2.5 7B Instruct 118.5 · Llama-3.1-8B-Instruct 116.4 · Gemma 3 4B IT 115.8
- Lowest priceQwen2.5 7B Instruct and Gemma 3 4B ITQwen2.5 7B Instruct $0.063 · Gemma 3 4B IT $0.063 · Llama-3.1-8B-Instruct $0.065 per 1M tokens (3:1 blend)
- Longest contextQwen2.5 7B Instruct and Gemma 3 4B ITQwen2.5 7B Instruct 131,072 · Gemma 3 4B IT 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsGemma 3 4B ITQwen2.5 7B Instruct: Text · Gemma 3 4B IT: Text, Images · 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 3 4B IT | Llama-3.1-8B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 34 | 35 |
| Price | 25% | 100 | 100 | 100 |
| Inputs & features | 15% | 25 | 50 | 25 |
| Context window | 10% | 25 | 25 | 24 |
| Overall | 100% | 50/100 | 52/100 | 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 3 4B ITGoogle | Llama-3.1-8B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 (best) | 115.8 | 116.4 |
| ECI rank | #159 of 165 (best) | #163 of 165 | #162 of 165 |
| GPQA DiamondGraduate-level science questions | 35.5% (best) | 23.2% | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.5% | 7.5% (best) | 1.7% |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.05 (best) | $0.06 |
| Output | $0.10 | $0.10 | $0.08 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.063 (best) | $0.063 (best) | $0.065 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 9 providers | Median of 17 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 131,072 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Open |
| API model ID | — | — | — |
| API providers | 4 | 10 | 18 (best) |
| Released | Sep 19, 2024 | Mar 12, 2025 | Jul 23, 2024 |
| Knowledge cutoff | — | Aug 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 3 4B IT$0.70
- Llama-3.1-8B-Instruct$0.76
Which should you choose?
Which is better: Qwen2.5 7B Instruct, Gemma 3 4B IT or Llama-3.1-8B-Instruct?
It is close. Our weighted score puts them within 2 points (Gemma 3 4B IT 52/100, Qwen2.5 7B Instruct 50/100, Llama-3.1-8B-Instruct 49/100), so choose by what matters most for your work: Qwen2.5 7B Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen2.5 7B Instruct, Gemma 3 4B IT 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). Gemma 3 4B IT costs $0.05 input / $0.10 output per million tokens (median across 9 API providers); Llama-3.1-8B-Instruct costs $0.06 input / $0.08 output per million tokens (median across 17 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 $0.063 for Gemma 3 4B IT (1× as much) and $0.065 for Llama-3.1-8B-Instruct (1× as much).
Which scores higher on benchmarks?
Qwen2.5 7B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 7B Instruct 118.5 (#159 of 165), Llama-3.1-8B-Instruct 116.4 (#162 of 165) and Gemma 3 4B IT 115.8 (#163 of 165). The confidence ranges of the top two overlap (110.6–121.2 vs 107.0–121.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 7B Instruct 35.5%, Llama-3.1-8B-Instruct 27.0%, Gemma 3 4B IT 23.2%; OTIS Mock AIME 2024–2025 — Gemma 3 4B IT 7.5%, Qwen2.5 7B Instruct 2.5%, Llama-3.1-8B-Instruct 1.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 7B Instruct, Gemma 3 4B IT and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 7B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen2.5 7B Instruct and Gemma 3 4B IT have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Gemma 3 4B IT up to 131,072, 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 3 4B IT accepts text and images; Llama-3.1-8B-Instruct accepts text. Gemma 3 4B IT handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Gemma 3 4B IT is the newest, released Mar 12, 2025. Qwen2.5 7B Instruct came out Sep 19, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Gemma 3 4B IT Aug 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.
