Glimpse vs SambaCloud

Glimpse

Glimpse reads images and video at $0.60 input and $3.00 output per million tokens, and OpenRouter serves it with tools, structured output and a 262,144-token context. It is a research preview with no public Elorian docs, model card or status page, and Elorian's terms allow training on submitted content unless a paid user opts out.

SambaCloud

Per-token prices and the model list are readable without a key at /v1/models, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7.

Glimpse

1. Call it through OpenRouter as elorian/glimpse at https://openrouter.ai/api/v1/chat/completions. Elorian's own API docs sit behind a console sign-in
2. Send video as a video_url content part, as a public URL or a base64 data URL. Batch requests are not available for this model
3. Set max_tokens yourself. The endpoint allows up to 256,000 output tokens, and visual reasoning spends many of them
4. Honour Retry-After on 429 and 503. With a single provider, a 503 means the Together deployment is unavailable, not that another host can take over
5. Treat counts and timestamps as unverified. Elorian's terms say outputs need independent human review before anyone relies on them

SambaCloud

1. Call GET https://api.sambanova.ai/v1/models at start-up and use only ids it returns. The docs name models the endpoint no longer lists
2. Read x-ratelimit-remaining-requests and x-ratelimit-remaining-requests-day on every response. The free tier allows 20 requests a day per model
3. Treat 429 queue_full and 503 maintenance as retryable after a delay, and 410 model_deprecated as a signal to change model
4. Validate JSON output yourself. Schema enforcement is best effort and strict: true changes nothing
5. Check max_completion_tokens per model. DeepSeek-V3.1 caps output at 7,168 tokens and Llama 3.3 70B at 3,072