{"name": "inference-net", "slug": "inference-net", "brand": {"name": "inference-net", "logo": null, "kind": "icon", "mono": false, "dark": null}, "timeline": {"date_min": "2026-09-17", "date_max": "2026-09-17", "changes": [], "endpoints": [{"slug": "z-ai2fglm-5.3-flash23inference-net2ffp4", "provider": "inference-net/fp4", "base": "inference-net", "providerSlug": "inference-net", "model": "z-ai/glm-5.3-flash", "modelSlug": "z-ai2fglm-5.3-flash", "methods": ["b3it"], "first": "2026-09-17", "last": "2026-09-17", "last_query": "2026-09-17", "n_changes": 0, "lt": null, "b3it": {"tv": [["2026-09-17", 0.11070707070707071]], "breaks": [], "changes": []}, "status": {"lt": "no_logprobs", "bi": "monitoring", "headline": "tracked", "headlines": ["tracked"], "ltCopy": "This endpoint does not return logprobs, so logprob tracking is impossible.", "biCopy": "This endpoint is actively monitored through its border inputs.", "ltDetail": null, "biDetail": null, "reason": "This endpoint is actively monitored through its border inputs."}}]}, "n_endpoints": 1, "n_active": 1, "n_models": 1, "n_variants": 1, "first": "2026-09-17", "last": "2026-09-17", "lt": {"endpoints": 0, "years": 0.0, "changes": 0, "rate": null, "ci": null}, "b3it": {"endpoints": 1, "years": 0.0, "changes": 0, "rate": null, "ci": null}, "variants": [{"name": "fp4", "n_endpoints": 1, "lt": {"endpoints": 0, "years": 0.0, "changes": 0, "rate": null, "ci": null}, "b3it": {"endpoints": 1, "years": 0.0, "changes": 0, "rate": null, "ci": null}}], "changes": [], "endpoints": [{"slug": "z-ai2fglm-5.3-flash23inference-net2ffp4", "model": "glm-5.3-flash", "modelSlug": "z-ai2fglm-5.3-flash", "org": "z-ai", "provider": "inference-net/fp4", "providerSlug": "inference-net", "methods": ["b3it"], "status": "stable", "lastChange": null, "recent": false, "nChanges": 0, "trace": [0.111], "changeFracs": [], "headline": "tracked", "headlines": ["tracked"], "ltStatus": "no_logprobs", "biStatus": "monitoring", "reason": "This endpoint is actively monitored through its border inputs."}, {"slug": "inference-net2fschematron-v2-small23inference-net", "model": "schematron-v2-small", "modelSlug": "inference-net2fschematron-v2-small", "org": "inference-net", "provider": "inference-net", "providerSlug": "inference-net", "methods": [], "status": null, "lastChange": null, "recent": false, "nChanges": 0, "trace": [], "changeFracs": [], "headline": "retired", "headlines": ["retired"], "ltStatus": "no_logprobs", "biStatus": "retired:no_bis", "reason": "Monitoring was retired: we could not find enough border inputs for this endpoint (since 2026-09-12)."}, {"slug": "inference-net2fschematron-v2-turbo23inference-net", "model": "schematron-v2-turbo", "modelSlug": "inference-net2fschematron-v2-turbo", "org": "inference-net", "provider": "inference-net", "providerSlug": "inference-net", "methods": [], "status": null, "lastChange": null, "recent": false, "nChanges": 0, "trace": [], "changeFracs": [], "headline": "retired", "headlines": ["retired"], "ltStatus": "no_logprobs", "biStatus": "retired:no_bis", "reason": "Monitoring was retired: we could not find enough border inputs for this endpoint (since 2026-09-12)."}, {"slug": "moonshotai2fkimi-k323inference-net2ffp4", "model": "kimi-k3", "modelSlug": "moonshotai2fkimi-k3", "org": "moonshotai", "provider": "inference-net/fp4", "providerSlug": "inference-net", "methods": [], "status": null, "lastChange": null, "recent": false, "nChanges": 0, "trace": [], "changeFracs": [], "headline": "too_expensive", "headlines": ["too_expensive"], "ltStatus": "no_logprobs", "biStatus": "too_expensive", "reason": "This endpoint costs more than our tracking budget allows."}, {"slug": "z-ai2fglm-5.323inference-net2ffp4", "model": "glm-5.3", "modelSlug": "z-ai2fglm-5.3", "org": "z-ai", "provider": "inference-net/fp4", "providerSlug": "inference-net", "methods": [], "status": null, "lastChange": null, "recent": false, "nChanges": 0, "trace": [], "changeFracs": [], "headline": "not_selected", "headlines": ["not_selected"], "ltStatus": "no_logprobs", "biStatus": "not_selected", "reason": "This endpoint vetted fine, but the selection budget went to more popular models."}]}