Falcon vs Llama vs Qwen — Open-Source AI Models Compared (2026)
May 2026 Update: Qwen 3.7 launched May 2026. See Qwen 3.7 Complete Guide for the latest.
Three ecosystems dominate open-source AI: Meta’s Llama (US), Alibaba’s Qwen (China), and TII’s Falcon (UAE). Each has different strengths, licensing, and model sizes. Here’s how they compare.
Head-to-head
| Falcon | Llama 4 | Qwen 3.5/3.6 | |
|---|---|---|---|
| Developer | TII (UAE) | Meta (US) | Alibaba (China) |
| Flagship | Falcon 2 11B / H1R 7B | Llama 4 Scout 70B | Qwen 3.6 Plus |
| Smallest useful | H1R 7B | Llama 4 8B | Qwen3 4B |
| Largest | 180B | 405B | 397B (MoE) |
| License | Apache 2.0 | Llama License (restrictive) | Apache 2.0 |
| Context | 8K-32K | 10M (Scout) | 1M (3.6 Plus) |
| Coding | Good | Good | ✅ Best |
| Reasoning | ✅ Strong (H1R) | Good | Good |
| Multilingual | Good | Good | ✅ Best (Chinese) |
| Ecosystem | Small | ✅ Largest | Large |
Licensing matters
| License | Falcon | Llama | Qwen |
|---|---|---|---|
| Commercial use | ✅ Unrestricted | ⚠️ Restricted (700M+ users need approval) | ✅ Unrestricted |
| Modify & distribute | ✅ Yes | ⚠️ With conditions | ✅ Yes |
| Type | Apache 2.0 | Custom (Llama License) | Apache 2.0 |
If licensing matters to your business, Falcon and Qwen (both Apache 2.0) are safer choices than Llama. Meta’s Llama License restricts companies with 700M+ monthly active users and has other conditions.
For coding
| Model | Size | Coding quality | Run locally |
|---|---|---|---|
| Qwen3-Coder 32B | 32B | ✅ Best | 24GB+ RAM |
| Qwen 3.6 Plus | API | ✅ Best (free) | API only |
| Llama 4 Scout 70B | 70B | Very good | 48GB+ RAM |
| Falcon H1R 7B | 7B | Good | 6GB RAM |
| Falcon 2 11B | 11B | Good | 8GB RAM |
Qwen dominates coding. Llama is strong but needs more hardware. Falcon is the budget option with surprisingly good reasoning.
For running locally on budget hardware
| RAM available | Falcon | Llama | Qwen |
|---|---|---|---|
| 6-8 GB | ✅ H1R 7B | Llama 4 8B | Qwen3 8B |
| 16 GB | Falcon 2 11B | Llama 4 8B | ✅ Qwen 3.5 27B (MoE) |
| 32 GB | Falcon 40B | Llama 4 Scout 70B (tight) | Qwen3-Coder 32B |
| 48 GB+ | Falcon 40B | ✅ Llama 4 Scout 70B | Qwen 3.5 397B (MoE) |
At 8GB, all three have competitive options. At 16GB, Qwen’s MoE architecture gives it an edge (27B total params, only 17B active). At 48GB+, Llama’s 70B dense model is the quality leader.
See our VRAM guide and best Ollama models for detailed recommendations.
Ecosystem and community
| Falcon | Llama | Qwen | |
|---|---|---|---|
| HuggingFace models | ~50 | ✅ 500+ | 200+ |
| Ollama support | ✅ | ✅ | ✅ |
| Fine-tuning community | Small | ✅ Largest | Large |
| Documentation | Good | ✅ Best | Good |
| Third-party tools | Limited | ✅ Most | Many |
Llama has the largest ecosystem by far. If you need fine-tuning resources, community support, and third-party integrations, Llama is the safest choice. Qwen is catching up fast, especially in the Chinese developer community.
Which to pick
| Situation | Pick | Why |
|---|---|---|
| Best coding model | Qwen 3.6 Plus | Free API, 78.8% SWE-bench |
| Largest ecosystem | Llama 4 | Most community support |
| Apache 2.0 license needed | Falcon or Qwen | No restrictions |
| Budget hardware (8GB) | Any — all have 7-8B models | Similar quality |
| Best reasoning at 7B | Falcon H1R | Hybrid architecture |
| Arabic support | Jais (not Falcon) | Purpose-built for Arabic |
| Chinese support | Qwen | Best Chinese model |
Also consider
Beyond these three, other strong open-source options:
- DeepSeek — best reasoning (R1), MIT license
- Yi — strong bilingual, Apache 2.0
- Gemma — Google’s open model, good quality
- Mistral/Devstral — EU-based, best for coding
Related: What is Falcon? · How to Run Falcon Locally · How to Run Llama 4 Locally · Qwen 3.6 Complete Guide · Yi vs Qwen vs DeepSeek · Best Open Source Coding Models