Speka API — live system status
What does this page show?
Speka is an AI API gateway that gives developers a single endpoint to access frontier models — chat completions, text embeddings, and image generation. This page is generated from real health checks: each model is called with an actual inference request on a schedule, and what you see below is the result of the most recent one.
Models running
20/23
1 degraded · 2 unavailable
Health-check success rate
87.12%
12,424 live checks recorded
Median response
573ms
across models that are up
Chat completions18 modelsDegraded
Embeddings4 modelsOperational
Image generation1 modelOperational
Model availability
Verified by calling each model for real — not by reading a vendor list.
| GLM 5.2 z-ai/glm-5.2 | Running· verified 11 min ago · 4493ms |
| Llama 3.1 8B Instruct meta/llama-3.1-8b-instruct | Running· verified 11 min ago · 202ms |
| Llama 3.2 3B Instruct meta/llama-3.2-3b-instruct | Running· verified 11 min ago · 160ms |
| Llama 3.3 70B Instruct meta/llama-3.3-70b-instruct | Unavailable· verified 11 min ago |
| MiniMax M3 minimaxai/minimax-m3 | Running· verified 11 min ago · 243ms |
| Mistral Nemotron mistralai/mistral-nemotron | Running· verified 11 min ago · 735ms |
| Nemotron 3 Ultra 550B nvidia/nemotron-3-ultra-550b-a55b | Running· verified 11 min ago · 971ms |
| Step 3.7 Flash stepfun-ai/step-3.7-flash | Running· verified 11 min ago · 410ms |
| GPT-OSS 20B openai/gpt-oss-20b | Running· verified 11 min ago · 365ms |
| Laguna XS 2.1 poolside/laguna-xs-2.1 | Unavailable· verified 11 min ago |
| Llama Nemotron Embed 1B v2 nvidia/llama-nemotron-embed-1b-v2 | Running· verified 11 min ago · 5858ms |
| Nemotron 3 Embed 1B nvidia/nemotron-3-embed-1b | Running· verified 11 min ago · 217ms |
| NV-Embed v1 nvidia/nv-embed-v1 | Running· verified 11 min ago · 247ms |
| NV-EmbedQA E5 v5 nvidia/nv-embedqa-e5-v5 | Running· verified 11 min ago · 225ms |
| FLUX.1 [dev] black-forest-labs/flux.1-dev | Running· verified 4h ago · 2689ms |
| Inkling thinkingmachines/inkling | Running· verified 11 min ago · 573ms |
| Nemotron 3 Nano 30B nvidia/nemotron-3-nano-30b-a3b | Running· verified 11 min ago · 677ms |
| Nemotron 3 Super 120B nvidia/nemotron-3-super-120b-a12b | Running· verified 11 min ago · 725ms |
| Nemotron Nano 9B nvidia/nvidia-nemotron-nano-9b-v2 | Running· verified 11 min ago · 665ms |
| Nemotron Super 49B nvidia/llama-3.3-nemotron-super-49b-v1.5 | Running· verified 11 min ago · 3360ms |
| Llama 3.2 11B Vision meta/llama-3.2-11b-vision-instruct | Running· verified 11 min ago · 282ms |
| Llama 3.2 90B Vision meta/llama-3.2-90b-vision-instruct | Degraded· verified 11 min ago |
| Nemotron Nano 12B VL nvidia/nemotron-nano-12b-v2-vl | Running· verified 11 min ago · 196ms |
Models that fail their live checks are removed from the public catalog automatically and restored when they recover. Machine-readable status is available on GET speka.me/v1/models.
FAQ
Frequently asked questions about Speka's reliability
When Speka's API gateway shows 'Operational,' all requests are routing normally across chat completions, embeddings, and image generation endpoints, and response times are within expected ranges. A status of 'Degraded' means elevated latency or partial errors — retry with exponential backoff. 'Outage' means the endpoint is unreachable and the team is actively investigating.
Speka does not rely on the upstream provider's model listing — a listed model can still fail on inference. Instead, every model in the catalog is probed on a schedule with a real request: a short chat completion, an embedding call, or a small image generation. The result (HTTP status, response time, and returned content) is what drives the status shown on this page, and models that fail repeatedly are removed from the public catalog automatically until they recover.
A 503 response means the service is temporarily unavailable. Implement exponential backoff — start at one second and double up to 30 seconds maximum — and retry the request. Check this status page for the current component health; most incidents resolve within minutes of detection. If a specific model shows as unavailable here, switch to another model with the same capability — your API key and base URL stay the same.
Chat completions accept a conversation thread and return a generated text response — used for dialogue, summarization, and instruction-following. Embeddings accept text and return a dense numeric vector used for semantic search, similarity ranking, and retrieval-augmented generation (RAG). The two serve different model types and are tracked separately on the status page.