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Models and pricing

Model IDs, context windows, input, cache and output prices.

Select a model by its API ID, not its display label. The table below loads current model metadata from the public API, including context size and separate input, cached-input, and output prices; without JavaScript or if the refresh fails, it retains a clearly dated fallback.

Discover model IDs

bash

curl --fail-with-body https://api.simplellm.eu/v1/models \
  -H "Authorization: Bearer $SIMPLELLM_API_KEY"

The OpenAI-compatible response contains data[].id, object, created, and owned_by. It does not include prices or a capability matrix.

Fetch pricing metadata

The public catalogue needs no API key:

bash

curl --fail-with-body https://simplellm.eu/api/models

Field	Meaning
`id`	Model ID to use in a request
`display_name`	Human-readable label; not necessarily the request ID
`context_length`	Advertised context size in tokens, or null
`price_sc_input`	SC per million uncached input tokens
`price_sc_cached`	SC per million cached input tokens; null uses the input price
`price_sc_output`	SC per million output tokens
`enabled` / `status`	Catalogue state; filter out disabled or planned entries
`throughput_tps`	Indicative throughput, or null; not guaranteed request speed

The current V1 catalogue has a known alias-filtering limitation: a listed alias can refer to a disabled backend model. Listing is not proof of readiness; handle unavailable-model errors rather than assuming every listed ID can immediately serve traffic.

Choose for your workload

Check the input context, expected output budget, token prices, and the features your integration needs. A large context window alone does not establish support for images, tool calling, or structured output.

Use a short representative request to validate model-specific behavior before a larger job. Do not benchmark production with bulk test traffic.

Context and cost

Conversation history is sent again with subsequent requests. Keep the system instructions and stable context ordered consistently when possible, but do not assume this guarantees a cache hit.

The maximum usable input depends on the model's context and output budget. Advertised context is not a promise that the entire window can be filled with input while still generating an arbitrary amount of output.

See billing for cache accounting and a worked cost example. Audio and image models are configured separately and have their own guides.

Model catalogue

Static fallback fetched 2026-09-14 from the public catalogue. The browser refreshes this table from the API on page load. Markdown and readers without JavaScript retain this dated fallback; fetch the public catalogue for current data. Only entries reported as enabled and available are included. Throughput is indicative, not an SLA.

Model ID	Context tokens	Input SC/M	Cache SC/M	Output SC/M	Approx tok/s
`DeepSeek-V4-Flash`	1048576	32	8	48	65
`DeepSeek-V4-Pro`	1048576	262	66	523	86
`gemma-4-E4B`	131072	0	0	0	49
`GLM-5.1`	202752	209	52	658	96
`GLM-5.2`	1048576	195	50	585	81
`glm-5.3-flash`	1048576	26	7	65	99
`gpt-oss-120b`	131072	16	16	83	47
`gpt-oss-20b`	131072	8	8	30	65
`Kimi-K2.6`	262144	150	37	598	97
`Kimi-K2.7-Code`	262144	163	40	585	170
`Kimi-K3`	1048576	390	100	1950	47
`Meta-Llama-3_3-70B-Instruct`	131072	139	139	139	26
`minimax-m3`	1048576	52	13	260	52
`Mistral-Nemo-Instruct-2407`	65536	27	27	27	30
`Mistral-Small-3.2-24B-Instruct-2506`	131072	18	18	58	14
`Qwen3-Coder-30B-A3B-Instruct`	262144	11	11	39	35
`Qwen3.5-397B-A17B`	262144	85	85	510	124
`Qwen3.5-9B`	262144	16	16	24	31
`Qwen3.6-27B`	262144	55	55	385	39
`qwen3.8-2.4t-a95b`	262144	325	82	780	—
`qwen3.8-flash-next`	262144	26	7	65	57