Qwen2.5-Coder-0.5B vs Llama-3.2-1B
Llama-3.2-1B comes out ahead, 36 to 24 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen2.5-Coder-0.5B
24/100- ECI88.2
- Price$0.10 / $0.10
- Context33K
- Our pick
MetaLlama-3.2-1B
36/100- ECI102.0
- Price$0.064 / $0.15
- Context131K
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Make it a three-way comparison.
Llama-3.2-1B is our pick
Llama-3.2-1B is the better all-round choice, scoring 36/100 against Qwen2.5-Coder-0.5B (24). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama-3.2-1BCapabilities Index (ECI): Llama-3.2-1B 102.0 · Qwen2.5-Coder-0.5B 88.2
- Lowest priceLlama-3.2-1BLlama-3.2-1B $0.085 · Qwen2.5-Coder-0.5B $0.10 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-1BLlama-3.2-1B 131,072 · Qwen2.5-Coder-0.5B 32,768 tokens
- Widest inputsSame inputsQwen2.5-Coder-0.5B: Text · Llama-3.2-1B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen2.5-Coder-0.5B | Llama-3.2-1B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 0 | 17 |
| Price | 25% | 97 | 100 |
| Inputs & features | 15% | 0 | 0 |
| Context window | 10% | 0 | 24 |
| Overall | 100% | 24/100 | 36/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen2.5-Coder-0.5BAlibaba (Qwen) | Llama-3.2-1BMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 88.2 | 102.0 (best) |
| ECI rank | #148 of 148 | #147 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 23.9% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 0.6% |
| Price per million tokens | ||
| Input | $0.10 | $0.064 (best) |
| Output | $0.10 (best) | $0.15 |
| Cached input | — | — |
| Blended (3:1) | $0.10 | $0.085 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 2 providers |
| Limits | ||
| Context window | 32,768 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | No | No |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | OpenLlama 3.2 Community License |
| API model ID | — | — |
| API providers | 1 | 2 (best) |
| Released | Nov 12, 2024 | Sep 25, 2024 |
| Knowledge cutoff | — | 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-Coder-0.5B$1.20
- Llama-3.2-1B$0.936
Which should you choose?
Which is better: Qwen2.5-Coder-0.5B or Llama-3.2-1B?
Llama-3.2-1B is the better all-round choice, scoring 36/100 against Qwen2.5-Coder-0.5B (24). It leads on capability, price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen2.5-Coder-0.5B or Llama-3.2-1B?
Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 API providers). Qwen2.5-Coder-0.5B costs $0.10 input / $0.10 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.085 per million tokens for Llama-3.2-1B versus $0.10 for Qwen2.5-Coder-0.5B (1.2× as much).
Which scores higher on benchmarks?
Llama-3.2-1B scores higher on the Capabilities Index (ECI): Llama-3.2-1B 102.0 (#147 of 148) and Qwen2.5-Coder-0.5B 88.2 (#148 of 148). The confidence ranges of the top two overlap (90.7–110.3 vs 61.3–100.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen2.5-Coder-0.5B and Llama-3.2-1B yet, so there is no like-for-like coding score. On overall capability, Llama-3.2-1B leads, which tends to carry over to coding, but test on your own codebase. Note that Qwen2.5-Coder-0.5B and Llama-3.2-1B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-1B has the largest context window at 131,072 tokens, against 32,768 for Qwen2.5-Coder-0.5B. Maximum output per response: Qwen2.5-Coder-0.5B up to 8,192, Llama-3.2-1B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen2.5-Coder-0.5B accepts text; Llama-3.2-1B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0 and Llama 3.2 Community License), so you can self-host them.
Which is newer?
Qwen2.5-Coder-0.5B is the newest, released Nov 12, 2024. Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-1B 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 Oct 4, 2026.
