AI Chatbot with Together AI on WordPress
SleekAI plugs into Together AI's OpenAI-compatible endpoint on https://api.together.xyz/v1, so a WordPress chatbot can run on any of the hundreds of open-weight models Together hosts - Llama 3.3, Mixtral, Qwen 2.5, DeepSeek, and more. Bring your own Together key.
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Hundreds of open models behind one API key
Together AI hosts a wide library of open-weight LLMs - Llama 3.3, Mixtral, Qwen 2.5, DeepSeek R1, Gemma, and dozens more - behind a single OpenAI-compatible API. For a WordPress chatbot, that breadth is the whole appeal. The same provider can run a 70B grounded-answer bot today and a fine-tuned 8B chat bot tomorrow with nothing more than a model string change in SleekAI's bot configuration.
SleekAI treats Together as a normal OpenAI-compatible provider. Set the base URL to https://api.together.xyz/v1, paste your Together API key, and pick the model string per bot. Common picks are meta-llama/Llama-3.3-70B-Instruct-Turbo, Qwen/Qwen2.5-72B-Instruct-Turbo, deepseek-ai/DeepSeek-R1, or mistralai/Mixtral-8x22B-Instruct-v0.1. Streaming, function calling, and JSON mode all behave exactly as they do on OpenAI.
Conversations land in wp_sleek_ai_chats with the Together model name and token counts logged, which makes evaluation across model families easy: clone a bot, swap the model string from Llama to Qwen to DeepSeek, leave the prompt unchanged, and compare logged conversations side by side. For teams that want to stay vendor-neutral on the model layer while keeping one billing relationship and one set of API keys, Together is the natural fit.
Workflow
Wire SleekAI to Together AI in four steps
Create a Together key
Add the provider
Pick a model per bot
Run A/B comparisons
Try it now
Ask the Together AI demo bot
Comparison
Generic chatbot vs SleekAI for Together AI
Generic chatbot
- Limited to closed-weight providers, no Together support
- Cannot run Llama, Qwen, DeepSeek, or Mixtral natively
- No way to A/B different open models on the same WordPress site
- Routes traffic through a vendor relay you cannot audit
- Bills marked up over Together's published per-token rate
SleekAI chatbot
- Native Together via OpenAI-compatible API
- Hundreds of open-weight models behind one key
- Llama 3.3, Mixtral, Qwen 2.5, DeepSeek R1, Gemma supported
- Streaming, function calling, and JSON mode all work
- Logs Together model name per chat for evaluation
Features
What SleekAI gives you for Together AI
Wide model library
One Together account exposes hundreds of open-weight models - Llama, Mixtral, Qwen, DeepSeek, Gemma, and family variants. SleekAI picks the exact model per bot, which makes the WordPress site model-agnostic at the bot layer.
Easy A/B model swaps
Clone a bot, change the Together model string, keep the prompt and display conditions identical, and compare logs side by side. Evaluation across model families goes from a one-week project to a one-minute experiment.
Open-weight pricing
Open-weight models on Together are typically cheaper per token than closed-weight frontier US models. High-volume marketing and support bots can sit on Qwen 2.5 or Llama 3.3 Turbo without breaking the monthly budget.
Use cases
Where Together plus SleekAI fits
Model evaluation
Teams that want a structured way to compare Llama, Qwen, Mistral, and DeepSeek on their own WordPress content run a clone-and-swap experiment across the same Together key over a couple of weeks.
Budget-sensitive sites
High-volume marketing, search, and support chat on smaller open-weight models. Pricing per million tokens often comes in well under what a comparable closed-weight tier costs on a US frontier provider.
Code-heavy chat
DeepSeek Coder, Qwen Coder, and other open-weight code-tuned models give technical docs sites a strong baseline for code-assistant chat without paying for a top-tier closed model on every reply.
The bigger picture
Why Together fits a model-agnostic strategy
Picking a single closed-weight provider for a WordPress chatbot used to be the easy choice, because the model gap between top-tier closed and best-available open-weight was wide enough that the conversation ended there. That gap closed in 2024 and is essentially gone for grounded chat in 2025 and 2026. Llama 3.3, Qwen 2.5, DeepSeek R1, and Mixtral variants all produce comparable answers on the WordPress use case - read a few injected posts and respond with a grounded paragraph plus a link - at a fraction of the cost of frontier US models.
The blocker that remained was integration overhead: standing up a Hugging Face deployment, paying for a separate inference cluster, or signing a contract with each provider separately. Together collapses all of that into one OpenAI-compatible endpoint, one key, and one bill, with hundreds of open-weight models behind it. SleekAI plugs into that endpoint with a base URL and an API key, and Multibot lets each chatbot on the WordPress install pick its own model string.
The end result is a chatbot stack that does not bet the whole strategy on a single vendor's quarterly roadmap. The cheapest model that does the job wins, and switching takes a minute instead of a quarter.
Questions
Common questions about SleekAI for Together AI
Together AI is a US-based inference provider that hosts hundreds of open-weight LLMs - Llama, Mixtral, Qwen, DeepSeek, Gemma, and many more - behind a single OpenAI-compatible API. One account and one key give you access to the whole library.
For grounded WordPress chat, meta-llama/Llama-3.3-70B-Instruct-Turbo is a strong default. For cheaper high-volume bots, the 8B Turbo variant works well. For long-context retrieval, Qwen2.5-72B-Instruct-Turbo is excellent. DeepSeek R1 is interesting for reasoning-heavy questions.
WordPress calls api.together.xyz directly using the bearer key from your Together account. There is no Sleek-hosted relay. Conversations land in wp_sleek_ai_chats on your own WordPress database with the Together model name logged per reply for traceability.
Yes, on the models that support them - most modern Llama, Qwen, and Mixtral instruct variants. SleekAI's tool-calling layer treats Together models like any other OpenAI-compatible provider, so bots that ground answers through custom tool calls keep working unchanged.
Yes. Multibot lets each chatbot pick its own model string. A common pattern is Llama 3.3 70B Turbo on the docs site for quality, Qwen 2.5 8B Turbo on the marketing pages for speed and cost, and DeepSeek R1 on a research-heavy bot - all from one Together key.
Together hosts a range of open embedding models such as togethercomputer/m2-bert-80M-2k-retrieval and BAAI/bge-large-en-v1.5. Configure those as a separate embeddings provider in SleekAI with the same base URL to build a fully Together-backed retrieval pipeline.
Open-weight models on Together generally cost significantly less per million tokens than comparable closed-weight tiers from US frontier labs. Exact rates change often - check the Together pricing page for current numbers - but on the smaller models the gap can be an order of magnitude.
Yes. If you fine-tune a model on Together, the resulting deployment exposes a normal model string. Paste that string into the SleekAI bot configuration and the WordPress chatbot starts using the fine-tune on the next request, no SDK changes required.
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