Qwen3.8 (open weights) alternatives: 9 tools compared (October 2026)

DeepSeek-V4.1-Flash is an open-weight multimodal mixture-of-experts model from DeepSeek, built for long contexts at lower memory cost and released under the MIT license.

Key functions

• Processes images and text natively
• Context of up to one million tokens
• Trained on agentic tasks

Compared with Qwen3.8 (open weights)

• Strong in the same markets as Qwen3.8 (open weights): China.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop. A model of this size needs a multi-GPU server; plan capacity before committing.

Qwen3-Coder-Next is an open-weight model from Alibaba's Qwen team built for coding agents and local development, combining a large total parameter count with only 3 billion active parameters for low running costs.

Key functions

• Long-horizon agent tasks with tool use and error recovery
• 256,000-token context
• Works with CLI and IDE tools such as Claude Code, Qwen Code and Cline

Compared with Qwen3.8 (open weights)

• Strong in the same markets as Qwen3.8 (open weights): China.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop. Review generated code before merging it.

Mistral Medium 3.5 is a multimodal model from the French developer Mistral AI, optimized for agentic and coding use cases and offered both through Mistral's API and as open weights under a modified MIT license.

Key functions

• Text and image understanding
• Function calling and structured outputs
• Document question answering and agents API

Compared with Qwen3.8 (open weights)

• Publishes a price (from $1.50 usage-based); Qwen3.8 (open weights) quotes on request.
• Can store data in the EU; Qwen3.8 (open weights) states no EU option.
• Headquartered in France, Qwen3.8 (open weights) in China.

Check before buying: Read the modified MIT license terms before self-hosting, since they differ from plain MIT. Some API features can temporarily transfer data outside the EU to listed subprocessors. Estimate token volumes, as billing is per token.

Command A+ is Cohere's current flagship language model, a sparse mixture-of-experts model with reasoning, vision and translation in 48 languages, available through Cohere's deployments and as open weights under Apache 2.0.

Key functions

• Reasoning with configurable thinking
• Image and text input
• 48 languages including all official EU languages

Compared with Qwen3.8 (open weights)

• Strongest elsewhere: Canada.

Check before buying: Ask Cohere for the current API price, since it was not on the pricing page at our check. Self-hosting needs at least one B200 or two H100 GPUs for the w4a4 version, more for fp8 and bf16, and your own operations team. Trial keys are free but rate limited and may not be used for production or commercial purposes.

IBM Granite 4 is a family of small open language models for business applications, released under Apache 2.0 in 3B, 8B and 30B sizes and backed by IBM's ISO 42001-certified AI management system.

Key functions

• Summarization, classification, extraction and question answering
• RAG and tool use for agents
• 12 languages including German

Compared with Qwen3.8 (open weights)

• Strongest elsewhere: United States.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop. The IP indemnification applies under IBM's contract terms, so check whether you use Granite via watsonx or only the open weights.

Gemma 4 is Google DeepMind's family of open-weight multimodal models in five sizes, with the smallest versions designed to run on laptops and mobile devices and the larger ones on workstations.

Key functions

• Text, image and on smaller models audio input
• Configurable thinking modes
• Function calling for agents

Compared with Qwen3.8 (open weights)

• Strongest elsewhere: United States.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop. On-device deployment still needs a plan for updates across all devices.

gpt-oss is OpenAI's family of open-weight language models for reasoning and agentic tasks, released under Apache 2.0 so companies can run them on their own hardware, including a smaller version for local use.

Key functions

• Configurable reasoning effort low, medium and high
• Function calling, web browsing and Python execution
• Fine-tunable

Compared with Qwen3.8 (open weights)

• Strongest elsewhere: United States.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop. The raw chain of thought is not intended for end users.

Mistral Small 4 is an open-weight mixture-of-experts model from French developer Mistral AI that combines general chat, reasoning and coding in one model and runs under the Apache 2.0 license.

Key functions

• Switch between instant replies and reasoning
• Text and image input
• Function calling and JSON output

Compared with Qwen3.8 (open weights)

• Headquartered in France, Qwen3.8 (open weights) in China.
• Strongest elsewhere: France.

Check before buying: Self-hosting means your team runs, secures and updates the model, including GPU capacity, monitoring and patching. Check the license terms for commercial use and keep a record of which version you deploy. If outputs feed decisions about people, a human must stay in the loop.