---
type: "post"
id: "gpt-6-1-sol-max-and-claude-fable-b17123"
slug: "gpt-6-1-sol-max-and-claude-fable-b17123"
title: "GPT 6.1 Sol (Max) and Claude Fable 5.1 (Max) take #2 and #3 on the leaderboard ."
description: "**Thesis:** A live agent leaderboard can make model comparisons more operational by pairing observed performance signals with task-cost estimates, but its ranking remains bounded by the platform’s sessions and methodology."
retrieval_nugget: "**Thesis:** A live agent leaderboard can make model comparisons more operational by pairing observed performance signals with task-cost estimates, but its ranking remains bounded by the platform’s sessions and methodology."
published_at: "2026-10-14"
updated_at: "2026-10-14"
record_date: "2026-10-14"
date_kind: "published_at"
topics: ["claude"]
source_urls: ["https://arena.ai/leaderboard/agent"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "post:gpt-6-1-sol-max-and-claude-fable-b17123"
status: "published"
visuals: []
editorial_provenance: {"schema_version":"newruntime-editorial-copy-v1","content_status":"source_grounded_final","final_copy_sha256":"sha256:cdf8f9298e52d7f35503949d603ccec1b402c573ca2fd63f3f951537afdd96a7","reviewed_at":"2026-10-14T05:02:39.026Z","source_evidence_count":1,"verified_claim_count":3,"site_analysis_schema_version":"newruntime-site-analysis-v1","site_object_kind":"field_note","observed_fact_count":3,"implication_count":2,"watch_condition_count":1,"related_record_count":0}
analysis: {"schema_version":"newruntime-site-analysis-v1","object_kind":"field_note","thesis":"A live agent leaderboard can make model comparisons more operational by pairing observed performance signals with task-cost estimates, but its ranking remains bounded by the platform’s sessions and methodology.","observed_facts":[{"text":"Agent Arena’s page dated Oct. 13, 2026 reports 2,555,192 sessions across 53 models.","source_urls":["https://arena.ai/leaderboard/agent"]},{"text":"The snapshot ranks Claude Opus 5.5 (Max) first, GPT 6.1 Sol (Max) second and Claude Fable 5.1 (Max) third.","source_urls":["https://arena.ai/leaderboard/agent"]},{"text":"The listed median task costs are $0.65 for GPT 6.1 Sol (Max) and $7.28 for Claude Fable 5.1 (Max).","source_urls":["https://arena.ai/leaderboard/agent"]}],"mechanism":"The mechanism is a platform-specific aggregation of session signals, not a universal measure of agent capability.","why_now":"The dated snapshot adds a direct comparison of current agent-session ranking and reported task costs.","implications":["Teams can use the figures to shortlist candidates for their own evaluations, not to assume the same rank or cost on their workloads.","A representative task set and local measurement can test whether observed quality and total cost transfer to a team's harness."],"evidence_boundary":"The source reports one dated leaderboard view and its own session-based signals; it does not show that results generalize across platforms, task distributions or configurations.","watch_conditions":["Watch whether subsequent snapshots retain these relative positions and whether the reported cost differences persist on comparable tasks."],"related_records":[],"new_branch_reason":"No prior New Runtime record was supplied for this leaderboard snapshot; this creates a distinct record of the dated ranking and its measured task-cost context."}
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
routes: {"html":"https://newruntime.com/posts/gpt-6-1-sol-max-and-claude-fable-b17123/","markdown":"https://newruntime.com/posts/gpt-6-1-sol-max-and-claude-fable-b17123.md","json":"https://newruntime.com/posts/gpt-6-1-sol-max-and-claude-fable-b17123.json"}
---

# GPT 6.1 Sol (Max) and Claude Fable 5.1 (Max) take #2 and #3 on the leaderboard .

## Retrieval answer

**Thesis:** A live agent leaderboard can make model comparisons more operational by pairing observed performance signals with task-cost estimates, but its ranking remains bounded by the platform’s sessions and methodology.

**Thesis:** A live agent leaderboard can make model comparisons more operational by pairing observed performance signals with task-cost estimates, but its ranking remains bounded by the platform’s sessions and methodology.

**Observed facts:** Agent Arena’s page, dated Oct. 13, 2026, reports 2,555,192 sessions across 53 models. It places Claude Opus 5.5 (Max) first, GPT 6.1 Sol (Max) second and Claude Fable 5.1 (Max) third. The page says its dynamic rankings use signals including task success, user satisfaction and steerability. It lists median task costs of $0.65 for GPT 6.1 Sol and $7.28 for Claude Fable 5.1.

**Mechanism:** The board aggregates outcomes from real Agent Arena sessions rather than presenting a single standardized benchmark score. **The mechanism is a platform-specific aggregation of session signals, not a universal measure of agent capability.** Pairing ranks with cost-per-task estimates gives teams a starting point for comparing observed outcomes and spend, while task mix, settings and sample selection can affect both.

**Why now:** **The dated snapshot adds a direct comparison of current agent-session ranking and reported task costs.** For builders choosing models, it foregrounds the trade-off between position on one dynamic ranking and the cost recorded in that environment, rather than treating rank alone as a deployment recommendation.

**Implications:** **Teams can use the figures to shortlist candidates for their own evaluations, not to assume the same rank or cost on their workloads.** A useful follow-up is to reproduce a representative task set and measure completion quality and total cost under the team’s own harness. **Watch whether subsequent snapshots retain these relative positions and whether the reported cost differences persist on comparable tasks.**

**Evidence boundary:** **The source reports one dated leaderboard view and its own session-based signals; it does not show that results generalize across platforms, task distributions or configurations.** No causal claim about model design or broad capability follows from these placements.

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

## Continue in the graph

Next records for an agent, linked to their Markdown twins. Replace `.md` with `.json` for structured fields, including `next_reads`.

- topic hub: [Claude](https://newruntime.com/topics/claude.md): Explore the claude topic hub.
- collection: [Field Notes](https://newruntime.com/posts.json): Open the latest editorial analysis.
- collection: [Source Ledger](https://newruntime.com/source-ledger.json): Inspect the public source evidence graph.
- whole graph: [discovery graph](https://newruntime.com/discovery-graph.json) (typed nodes and edges) and [site index](https://newruntime.com/site-index.md)