# Pricing

> How sference bills inference: per-token rates for every catalog model across the realtime, flex, and batch windows, cached input, and what counts as a token.

Source: https://sference.com/docs/pricing

sference bills **per token**. There is no platform fee, no seat cost, and no minimum spend on serverless: you pay for prompt tokens and completion tokens. Dedicated capacity is billed per GPU-hour instead — see [Deployments](https://sference.com/docs/deployments).

All rates are **USD per 1M tokens**. The site shows the same numbers with a EUR toggle.

## Three windows, three prices

Every request runs on one of three scheduling windows. The window decides how long the request may wait behind other work, and therefore the rate.

| Window | How you select it | Wait budget | Rate |
| --- | --- | --- | --- |
| **realtime** | default; sync `/v1/chat/completions`, `/v1/messages`, or blocking `/v1/responses` | none — served as soon as capacity allows | list |
| **flex** | `service_tier: "flex"` on `/v1/chat/completions` or `/v1/responses` | up to 30 minutes, best effort | **0.7 × list** |
| **batch** | `background: true`, batches, or streams (`completion_window: "24h"`) | up to 24 hours | **0.5 × list** |

Realtime, flex, and batch are **scheduling priorities on the same fleet**, not separate deployments. Interactive traffic never queues behind backfill, which is what makes the discounted windows possible without degrading realtime.

> **Flex is per-account**
>
> `service_tier: "flex"` must be enabled on your account. Ask your account team to turn it on. A flex request that cannot complete inside its window fails with `408`, and the OpenAI SDKs retry it automatically.

Flex and batch are **independent dimensions** and they stack: a batch request submitted with `service_tier: "flex"` bills at `0.7 × 0.5 = 0.35 ×` list.

## Catalog rates

USD per 1M tokens. **Cached input** is the rate for prompt tokens served from the prefix cache — see [Prompt caching](https://sference.com/docs/guides/prompt-caching).

| Model | Window | Input | Cached input | Output |
| --- | --- | ---: | ---: | ---: |
| `moonshotai/Kimi-K3` | realtime | 3.00 | 0.45 | 15.00 |
| | flex | 2.10 | 0.315 | 10.50 |
| | batch | 1.50 | 0.225 | 7.50 |
| `zai-org/GLM-5.3` | realtime | 1.20 | 0.26 | 4.20 |
| | flex | 0.84 | 0.182 | 2.94 |
| | batch | 0.60 | 0.13 | 2.10 |
| `zai-org/GLM-5.2` | realtime | 1.20 | 0.26 | 4.20 |
| | flex | 0.84 | 0.182 | 2.94 |
| | batch | 0.60 | 0.13 | 2.10 |
| `deepseek-ai/DeepSeek-V4.1-Flash` | realtime | 0.50 | 0.05 | 1.50 |
| | flex | 0.35 | 0.035 | 1.05 |
| | batch | 0.25 | 0.025 | 0.75 |
| `deepseek-ai/DeepSeek-V4-Flash-0731` | realtime | 0.28 | 0.07 | 0.56 |
| | flex | 0.196 | 0.049 | 0.392 |
| | batch | 0.14 | 0.035 | 0.28 |
| `deepseek-ai/DeepSeek-V4-Flash` | realtime | 0.28 | 0.07 | 0.56 |
| | flex | 0.196 | 0.049 | 0.392 |
| | batch | 0.14 | 0.035 | 0.28 |
| `Cloudflare/clef` | realtime | 0.24 | — | 0.00 |
| | flex | 0.168 | — | 0.00 |
| | batch | 0.12 | — | 0.00 |
| `zai-org/GLM-5.3-Flash` | realtime | 0.20 | 0.07 | 0.60 |
| | flex | 0.14 | 0.049 | 0.42 |
| | batch | 0.10 | 0.035 | 0.30 |

`Cloudflare/clef` has no output charge — it is a decisions model and bills on input only.

> **This table is a snapshot**
>
> `GET https://api.sference.com/v1/models` is authoritative and reflects your entitlements, including custom models. Rates for models agreed in your contract are per contract. Read the API at runtime rather than hardcoding this table.

## What counts as a token

- **Input** — every token in the prompt, including system messages, tool definitions, and images converted to tokens. Tokens served from the prefix cache bill at the **cached input** rate instead.
- **Output** — every generated token, **including reasoning tokens**. A model that thinks for 2,000 tokens before answering 100 bills 2,100 output tokens. This is why `max_output_tokens` matters on reasoning models: the cap covers the thinking too.
- **No cache-write charge.** Unlike some providers, sference does not bill a premium for writing into the prefix cache, and no TTL choice changes the price. Cached tokens are simply cheaper.
- **Rejected requests are not billed.** A `max_queue_wait_exceeded` rejection, a `408` on flex, or an upstream failure before any output costs nothing. A request that produced output and then failed bills for the tokens it produced.

## Checking what you spent

| Surface | What it shows |
| --- | --- |
| `GET /control/v1/billing/summary` | Current period spend, balance, and burn rate |
| `GET /control/v1/usage/summary` | Token and cost totals, optionally grouped by model, key, or member |
| `GET /control/v1/activity` | Per-request rows: model, tokens, cost, latency, outcome |

See [Usage & analytics](https://sference.com/docs/usage) for the full endpoint list, CSV exports, and attribution.

## Dedicated and enterprise

- **Dedicated deployments** — reserved GPU capacity with private endpoints, billed per GPU-hour on monthly commitments. Predictable latency and no per-token metering. See [Deployments](https://sference.com/docs/deployments).
- **Custom models** — fine-tunes and distilled models are hosted under an enterprise agreement; pricing is per contract. See [Custom models](https://sference.com/docs/custom-models).
- **Enterprise** — annual agreements, committed-spend discounts, volume pricing, and custom SLAs. Contact `hello@sference.com`.

## Why per-token beats self-managed

The per-token rate is only comparable to self-hosting if your GPUs are busy. Our scheduler keeps utilization high around the clock by packing realtime traffic and batch backfill onto the same fleet; on self-managed instances or an on-prem cluster, idle capacity is paid for whether it serves tokens or not. The rate you see is the cost of the tokens, not the cost of the reservation.

- [Pricing for agents](https://sference.com/docs/pricing-for-agents): The same rates as a compact Markdown table, for agents and exports.
- [Prompt caching](https://sference.com/docs/guides/prompt-caching): Cached input is the largest lever on most bills.
- [Usage & analytics](https://sference.com/docs/usage): Attribute spend to a workload, key, or team member.