Open-Source LLMs With an API
As of August 2026, AIDiveForge tracks 6 open-source llms with an api. The top three by verified-data score are Qwen-Image-3.0, DBRX Instruct, and DeepSeek V3. Curated open-source llms with an api tracked by AIDiveForge. Listings are verified against each tool's live website and re-checked regularly.
Last updated July 26, 2026 · 6 tools
Ranked by AIDiveForge's verified-data score: data completeness, verification recency, community rating, and real visitor engagement. How we rank · No tool can pay for placement.
1. Qwen-Image-3.0
The family spans four distinct problem areas: safety moderation via Qwen3Guard, multilingual translation via Qwen-MT, text-rich image generation and editing via Qwen-Image and Qwen-Image-Edit, and general reasoning via the base Qwen3 models. Self-hosting is a real option — weights are published on Hugging Face and ModelScope, and the Apache-2.0 license means no legal friction for commercial deployment. Qwen-MT's hosted API is a paid-only feature, so teams that want translation without infrastructure management pay for access; everyone else runs inference themselves. The research layer is also public: GSPO, the vendor's proposed fix for RL training instability in large models, is documented and available for teams experimenting with fine-tuning at scale.
PaidOpen SourceAPISelf-hostedVerified Jul 26, 2026
2. DBRX Instruct
DBRX Instruct is a free, open-source large language model built by Databricks for instruction-following tasks in software development and enterprise applications. It uses a mixture-of-experts architecture to balance performance with efficiency, and integrates natively with Databricks' data platform—a meaningful advantage if you're already in that ecosystem. The model shows strong results on coding and reasoning benchmarks, but carries real limitations: no vision capabilities, a shorter context window than Claude or GPT-4, and less real-world adoption in mainstream enterprise settings. For teams deeply embedded in Databricks infrastructure, it's a compelling option; for everyone else, it remains a secondary choice.
FreeOpen SourceAPISelf-hosted32.8k tokens context$1.2/1M inputVerified Apr 8, 2026
3. DeepSeek V3
A fast, chat-based, Mixture-of-Experts (MoE) model from DeepSeek.
PaidOpen Source$0.14 per million input tokens and $0.28 per million output tokensAPISelf-hosted131.1k tokens context$0.28/1M inputVerified May 15, 2026
4. Llama 3
Llama 3 is a large language model family designed to handle standard NLP workloads—text generation, translation, summarization, and sentiment analysis—across a range of scales. Meta released it as open source, meaning you can download weights, fine-tune locally, or run it on your own infrastructure instead of hitting an API. The catch: while free to use, the model is young relative to Llama 2, and local deployment requires real hardware or cloud credits. For teams building production systems, this trades managed convenience for control and lower long-term marginal costs.
FreeOpen SourceAPISelf-hosted8.2k tokens context$2.65/1M input
5. Mistral
Mistral offers a family of large language models ranging from the lightweight Mistral 7B to the more capable Mistral Large, accessible both as open-source downloads and via paid API. The company positions itself as the cost-conscious alternative to ChatGPT and Claude, with a free tier covering basic use cases but throttled requests that frustrate serious users. Pricing for the API starts around $0.14 per million input tokens—roughly one-third OpenAI's rate—making it genuinely cheap at scale. The catch: public API documentation remains sparse, and the free tier's limitations mean you'll likely hit a paywall faster than expected.
FreeOpen SourceAPISelf-hosted32k tokens context$0.15/1M input
6. Qwen
Qwen covers text generation, coding assistance, multimodal understanding, and reasoning tasks across a range of model sizes, all under Apache-2.0 licensing, which means you can run it locally, fine-tune it, and ship it in a product without negotiating an enterprise agreement. The architecture is a Transformer decoder, so the fine-tuning toolchain your team already knows applies directly. Multilingual capability is a documented design goal, not a side effect, making it a practical choice for teams building outside English-first markets. The Qwen Studio interface offers free access for experimentation, while production-scale API usage routes through Alibaba Cloud — meaning your infrastructure story depends on which cloud you already operate in. Teams needing sovereign deployment or cost-controlled inference can self-host, but that path requires operational capacity the vendor does not manage for you.
PaidOpen SourceAPISelf-hostedVerified Jun 24, 2026
Listings on this page are sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent — no money changes hands for inclusion.