Published: May 15, 2026 Β· Updated: July 2026
Open-Weight LLM Landscape 2026: MiMo vs DeepSeek vs Qwen vs Llama 4 vs Mistral
The open-weight LLM landscape in 2026 has consolidated around five major families: Xiaomi MiMo, DeepSeek, Alibaba's Qwen, Meta's Llama 4, and Mistral AI. Each represents a distinct philosophy about what open-weight AI should be β and each has different strengths depending on your use case.
This guide compares all five across seven dimensions: architecture, licensing, benchmark performance, API pricing, edge deployability, ecosystem, and community support.
1. Architecture Comparison
| Family | Flagship Model | Architecture | Active Params | Context |
|---|---|---|---|---|
| MiMo | V2.5-Pro | MoE + Hybrid Attention | 1T+ (est.) | 1M |
| MiMo | V2-Flash | MoE | 15B / 309B total | 56k |
| DeepSeek | V4 Pro | MoE | 37B / 671B total | 128k |
| Qwen | Qwen2.5-72B | Dense | 72B | 128k |
| Llama 4 | Llama 4 Maverick | Open-weight multimodal | Undisclosed | β |
| Mistral | Mistral Large 3 | Dense | Undisclosed | 262k |
Key takeaway: MoE architectures dominate the high-end. MiMo-V2-Flash leads on efficiency (highest ratio of active-to-total parameters at 5%). Llama 4 Maverick is a multimodal open-weight model competitive with GPT-5.5 class.
2. Licensing
| Model | License | Commercial Use | Restrictions |
|---|---|---|---|
| MiMo (all) | MIT | β Unlimited | None |
| DeepSeek-R1 | MIT | β | None |
| DeepSeek-V4 Pro | MIT | β | None |
| Qwen2.5 | Apache 2.0 | β | Attribution required |
| Llama 4 | Custom | β | Usage-based (varies) |
| Mistral Large 3 | Apache 2.0 | β | Attribution required |
Key takeaway: MiMo and DeepSeek offer the most permissive licensing (MIT). Llama 4's custom license includes usage-based restrictions β relevant mainly for large-scale deployments.
3. Benchmark Performance
| Model | SWE-Bench | License |
|---|---|---|
| MiMo-V2-Flash | 73.4% | MIT |
| DeepSeek-R1 | 68.3% | MIT |
| Claude Opus 4.5 | 76.80% | Closed |
| DeepSeek-V4 Pro | Improved over V3 (39%) | MIT |
On AIME 2024 (math reasoning at 7B scale): MiMo-7B-RL leads at 68.2%, ahead of DeepSeek-R1-7B (65.4%) and Qwen2.5-Math-7B (62.0%).
Key takeaway: MiMo-V2-Flash holds the highest SWE-Bench score among open-weight models. The margin over DeepSeek-R1 (5.1 percentage points) is significant on a benchmark that measures real-world coding ability. Among closed-source models, Claude Opus 4.5 (76.80%) and Claude Opus 4.8 (~80.9%) lead.
4. API Pricing
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| MiMo-V2.5-Pro | $1.00 | $3.00 |
| MiMo-V2-Flash | $0.50 | $1.50 |
| DeepSeek-V4 Pro | $0.435 | $0.87 |
| DeepSeek-R1 | $0.55 | $2.19 |
| Qwen2.5-72B (via API) | $0.90 | $2.70 |
| Llama 4 (via Together) | β | β |
| Mistral Large 3 | $2.00 | $6.00 |
Key takeaway: DeepSeek-V4 Pro is the cheapest per-token (June 2026 price cut). MiMo is mid-range but offers the best SWE-Bench score per dollar. Self-hosting changes the economics completely β with MIT licensing, all open-weight models effectively cost the same (hardware only).
5. Edge Deployability
This is where MiMo separates from the pack. MiMo-7B at INT4 (3.5GB) runs on phones, smart speakers, and car cockpits. No other flagship family matches this:
- MiMo: 7B at 3.5GB (INT4). Deployable on Snapdragon 8 Gen 4, Xiaomi NPU, ARM CPUs.
- DeepSeek: No edge-optimized model. R1-7B exists but without INT4 tooling.
- Qwen: 2.5-7B available; no INT4 quantization toolkit.
- Llama 4: Maverick is multimodal, not specifically optimized for edge.
- Mistral: 7B available; Nemo 12B is next closest but requires >8GB.
6. Ecosystem and Integration
- MiMo: MiMo Code (coding agent), HuggingFace, GitHub, OpenAI-compatible API, VS Code extension, Cursor/Cline/Zed support
- DeepSeek: DeepSeek Coder, Chat platform, API, active research community
- Qwen: Alibaba Cloud integration, Tongyi Qianwen app, strong Chinese-language corpus
- Llama 4: Meta suite, broadest ecosystem (AWS, GCP, Azure, HuggingFace, Ollama), fine-tuning tools, safety benchmarks
- Mistral Large 3: Le Chat, Mistral API, enterprise-focused, strong EU presence
Selection Guide
Choose MiMo if: You need edge deployment, MIT licensing, or the best coding benchmarks. MiMo is the strongest choice for agentic applications and on-device inference.
Choose DeepSeek if: You need the cheapest API pricing and 128k context. DeepSeek-V4 Pro offers excellent value per token after the June 2026 price cut.
Choose Qwen if: You serve Chinese-language users or need multimodal capabilities. Qwen's VL and audio models are mature.
Choose Llama 4 if: You need the broadest ecosystem support, mature fine-tuning tools, and large-scale cloud deployment.
Choose Mistral if: You're EU-based and need GDPR-compliant hosting, or need Mistral Large 3 for enterprise-facing applications.