Abliterated API Observatory
Model dossier

GLM 5.3 Flash Abliterated: price the workload, then measure the fit

GLM 5.3 Flash Abliterated has a straightforward budget case: the published rates produce a $2.96 inference subtotal for the example below. The Flash name alone should not determine latency expectations. This record uses catalog prices verified on 11 November 2026 and the saved public performance window ending on 10 November at 23:35:03 UTC.

By Abliterated API Observatory · 11 November 2026

Fix the edition and interface first

The catalog identifier is glm-5.3-flash-abliterated. Both context and output ceilings are listed as 1,048,576 and 131,072 tokens, respectively. Preserve that full ID in evaluation records so results do not accidentally mix different editions.

The documented route is POST https://uncensuredai.com/v1/chat/completions with Bearer authentication. Endpoint compatibility does not by itself confirm every client feature. No live inference or maximum-context test was performed for this dossier.

Calculate the uncached baseline

Rates per million tokens are $0.22 input, $0.80 output, $0.08 cache read and $0.22 cache write. Eight million uncached input tokens cost $1.76; 1.5 million output tokens cost $1.20. The resulting $2.96 subtotal excludes cache operations, retries and other charges.

Track input and output separately in the workload being evaluated. A low input rate alone cannot predict the bill when response lengths or retry frequency change.

Read the observed speed with its outcome context

The public snapshot reports 45.84 token/s with 98.39% success, alongside 38168 ms average request latency. The observation window is 10 November 2026, 00:00:00–23:35:03 UTC. It contains the current partial hour plus 23 complete hourly buckets.

The summary does not provide request volumes or a breakdown of prompt shapes and parallel load. Those omissions prevent a controlled ranking against GLM 5.3 or other models. The figures also do not measure time to first token, so reported success should remain beside throughput in any interpretation.

Make the acceptance test useful

Choose representative prompts with known acceptance criteria: extraction accuracy, response format, instruction adherence or whatever the application actually needs. Fix generation settings, record input/output lengths, and measure both sequential use and intended concurrency. Preserve errors and retry counts in the results.

Test function calling, structured outputs and image inputs explicitly if required; none was verified here for this exact Abliterated edition. For streaming, measure first-token time separately from full-request duration. Publish sample size, task success and cost per accepted result.

UncensuredAI states that capacity is shared, HTTP 429 responses may occur, and no fixed RPM or TPM allowance is guaranteed. Your pilot should establish whether available capacity and response behavior match the product you intend to ship.

Use the published rates as the baseline and the API documentation as the connection reference. Acceptance depends on measured task results, not the Flash label or the low baseline alone.

Put the idea to work.

Review the current UncensuredAI catalog and create an API key when you are ready to run your own evaluation.

Sources and scope

Prices are USD per million tokens unless stated otherwise. Sources checked 11 Nov 2026. Editorial standards and methodology: see the method page.