A review observatory for abliterated APIs. Compare GLM and DeepSeek editions through published prices, exact model identifiers and dated provider-reported performance.
deepseek-v4.1-flash-abliteratedglm-5.3-flash-abliteratedglm-5.3-abliteratedInspect both before choosing an endpoint. A model’s name alone does not establish its speed, features or exact behavior.
| Model / edition | Input | Output | Observed token/s | API model ID |
|---|---|---|---|---|
| DeepSeek V4.1 FlashAbliterated | $0.27 | $0.95 | 151.69 | deepseek-v4.1-flash-abliterated |
| GLM 5.3 FlashAbliterated | $0.22 | $0.80 | 45.84 | glm-5.3-flash-abliterated |
| GLM 5.3Abliterated | $0.70 | $1.95 | 134.84 | glm-5.3-abliterated |
No matching models. Try a different name or collection.
Provider-reported aggregate, 10 Nov 2026, 00:00–23:35 UTC. Snapshot of the public 24-hour summary; not a guaranteed speed or an independent benchmark. Sample counts are not published. Performance source.
A published listing establishes the offered model ID and rates, not the behavior of your completed integration. Test each required capability and record the result against the exact edition.
Use the capability checklistUncensuredAI states that it does not retain API prompts, responses or chat content on its servers. Account data is separate; connected apps have their own storage settings. Read the retention scope.
Inspect your own gateway, observability and customer app too. A provider policy does not configure those components for you.
Assess GLM 5.3 Abliterated using its exact model ID, published token prices, context limits and dated throughput and success observations.
Read the guideA buying dossier for GLM 5.3 Flash Abliterated with token prices, a $2.96 workload example, exact API ID and contextualized performance data.
Read the guideReview DeepSeek V4.1 Flash Abliterated using its exact API ID, $2.57 example workload, published limits and dated 151.69 token/s observation.
Read the guideCompare three Abliterated API editions using documented IDs, prices, context limits and dated throughput plus success, with a reproducible acceptance method.
Read the guide