Qwen2.5 7B Instruct vs Llama 4 Scout 17B Instruct
Llama 4 Scout 17B Instruct comes out ahead, 62 to 44 on our weighted score, though Qwen2.5 7B Instruct is 10% cheaper per token.
Alibaba (Qwen)Qwen2.5 7B Instruct
44/100- ECI118.5
- Price$0.175 / $0.70
- Context131K
- Our pick
MetaLlama 4 Scout 17B Instruct
62/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
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Llama 4 Scout 17B Instruct is our pick
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Qwen2.5 7B Instruct (44). It leads on capability, inputs & features and context window. Qwen2.5 7B Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama 4 Scout 17B InstructCapabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 · Qwen2.5 7B Instruct 118.5
- Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.306 · Llama 4 Scout 17B Instruct $0.341 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · Qwen2.5 7B Instruct 131,072 tokens
- Widest inputsLlama 4 Scout 17B InstructQwen2.5 7B Instruct: Text · Llama 4 Scout 17B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen2.5 7B Instruct | Llama 4 Scout 17B Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 52 |
| Price | 25% | 74 | 72 |
| Inputs & features | 15% | 25 | 50 |
| Context window | 10% | 24 | 100 |
| Overall | 100% | 44/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen2.5 7B InstructAlibaba (Qwen) | Llama 4 Scout 17B InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 118.5 | 129.7 (best) |
| ECI rank | #141 of 148 | #126 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 35.5% | 51.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.5% | 7.8% (best) |
| Price per million tokens | ||
| Input | $0.175 (best) | $0.225 |
| Output | $0.70 | $0.69 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.306 (best) | $0.341 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 4 providers |
| Limits | ||
| Context window | 131,072 tokens | 10,000,000 tokens (best) |
| Max output | 8,192 tokens | 16,384 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | qwen2-5-7b-instruct | — |
| API providers | 1 | 4 (best) |
| Released | Sep 19, 2024 | Apr 5, 2025 |
| Knowledge cutoff | Apr 2024 | Aug 2024 |
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$3.15
- Llama 4 Scout 17B Instruct$3.63
Which should you choose?
Which is better: Qwen2.5 7B Instruct or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Qwen2.5 7B Instruct (44). It leads on capability, inputs & features and context window. Qwen2.5 7B Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen2.5 7B Instruct or Llama 4 Scout 17B Instruct?
Qwen2.5 7B Instruct is cheaper at $0.175 input / $0.70 output per million tokens (official Alibaba API price). Llama 4 Scout 17B Instruct costs $0.225 input / $0.69 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.306 per million tokens for Qwen2.5 7B Instruct versus $0.341 for Llama 4 Scout 17B Instruct (1.1× as much).
Which scores higher on benchmarks?
Llama 4 Scout 17B Instruct scores higher on the Capabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 (#126 of 148) and Qwen2.5 7B Instruct 118.5 (#141 of 148). Their confidence ranges do not overlap (124.8–131.4 vs 110.7–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Llama 4 Scout 17B Instruct 51.8%, Qwen2.5 7B Instruct 35.5%; OTIS Mock AIME 2024–2025 — Llama 4 Scout 17B Instruct 7.8%, Qwen2.5 7B Instruct 2.5%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5 7B Instruct and Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, Llama 4 Scout 17B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 131,072 for Qwen2.5 7B Instruct. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Llama 4 Scout 17B Instruct up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5 7B Instruct accepts text; Llama 4 Scout 17B Instruct accepts text and images. Llama 4 Scout 17B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Llama 4 Scout 17B Instruct is the newest, released Apr 5, 2025. Qwen2.5 7B Instruct came out Sep 19, 2024. Knowledge cutoff: Qwen2.5 7B Instruct Apr 2024, Llama 4 Scout 17B Instruct Aug 2024.
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 Oct 4, 2026.
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