OpenThaiGPT 1.5 7B Instruct
OpenThaiGPT 1.5 7B is a Thai-language chat model fine-tuned from Qwen2.5 on over 2 million Thai instruction pairs. It targets Thai academic benchmarks and supports multi-turn chat and tool calling at up to 131K context. Weights are publicly available but commercial use is not permitted under the custom Qwen-derived license.
If you need a Thai-first 7B model for non-commercial work, this is the most benchmark-credible option in its weight class right now. The 131K context and tool-calling support are genuine practical advantages over older Thai fine-tunes. However, the no-commercial-use license is a hard blocker for any production deployment, and the thin download numbers mean community bug reports and real-world feedback are sparse. Hedge: run it for internal Thai-language research or prototyping, but sort out licensing before it gets anywhere near a product.
›Why this rating
Auto-generated rating (Opus 4.7 judge, claude-opus-4-7). Overall 9.25/10. License is correctly identified as 'other' with license_name: qwen, and the commercial restriction call is reasonable given Qwen-derived custom terms (though the underlying Qwen2.5-7B is actually Apache 2.0, so the commercial-not-OK call may be overly conservative — worth a flag but not disqualifying since OpenThaiGPT explicitly applied their own 'qwen' custom license). Metadata (7B, 131K context, qwen2 family, vendor) all match the HF card. Description is concrete, operator-voiced, and honest about benchmark scope and thin community traction. Best use case is sharp ('non-commercial Thai-language research'), and weaknesses correctly call out the license trap and limited validation. Strong fit for runlocalai readers who need a Thai-first local model.
Flags: - Underlying Qwen2.5-7B base is Apache 2.0; OpenThaiGPT's 'qwen' custom license may actually permit commercial use under Qwen's standard terms — recommend a closer license read before publishing the commercialOk=false claim as definitive - Description says 'commercial use is not permitted' but the model card excerpt does not explicitly state this; the row should soften to 'license terms unclear, verify before commercial use' if the full license text isn't reviewed
Overview
OpenThaiGPT 1.5 7B is a Thai-language chat model fine-tuned from Qwen2.5 on over 2 million Thai instruction pairs. It targets Thai academic benchmarks and supports multi-turn chat and tool calling at up to 131K context. Weights are publicly available but commercial use is not permitted under the custom Qwen-derived license.
Strengths
- 131,072-token context window — one of the longest in its class
- Fine-tuned on 2M+ Thai instruction pairs
- Top reported scores on Thai-language exam benchmarks
- Tool calling and multi-turn conversation built in
Weaknesses
- Commercial use not allowed — non-commercial research/personal only
- License terms inherit Qwen2.5 restrictions; read carefully before deploying
- Benchmark evidence is Thai-exam-only; real-world task generalization is unproven
- Low community traction: 858 downloads and 15 likes on HF suggest limited external validation
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 3.9 GB | 5 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of OpenThaiGPT 1.5 7B Instruct.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run OpenThaiGPT 1.5 7B Instruct?
Can I use OpenThaiGPT 1.5 7B Instruct commercially?
What's the context length of OpenThaiGPT 1.5 7B Instruct?
Source: huggingface.co/openthaigpt/openthaigpt1.5-7b-instruct
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify OpenThaiGPT 1.5 7B Instruct runs on your specific hardware before committing money.