vibetest

Synthesizing Moonshot AI's 47-benchmark launch suite for Kimi K3.1 Pro (2.8T total / 104B active MoE open-weight model) with independent evaluations from Artificial Analysis (Intelligence Index v4.3.2), Epoch AI (ECI, FrontierMath, GPQA), Terminal-Bench 4.0, LMArena, Vals AI, LiveBench 2.0, and ARC-AGI-2.

Composite Score Gap (AA v4.3.2)

−2.53 pts (−4.4%)

Kimi K3.1 Pro scores 55.09 (#4 globally) vs. Claude Opus 5.5 at 57.62 (#1), beating GPT-6 Astra (52.67) & Gemini 4 Argon (52.56).

Horizontal Frontier Time-Lag

1.0 to 4.5 mos

1.02 mos (31 days) on AA v4.3.2 (matching Opus 5.5, Sep 22) vs. ~4.5 mos [1.7–6.0m] projected on science/math-heavy Epoch ECI.

Bifurcated Domain Split

+3.5 to −29.0 pts

Leads AA Terminal-Bench 4.0 (67.2% vs 63.6%) & 1M Context (86.3%), but trails by −29.0 pts on Terminal-Bench Science & −26.4 pts on HLE-Diamond.

Open-Weight & Cost Advantage

+16.2 pts | 2.8× Cheaper

Leads best Western open-weight model (Muse Spark Open, 38.87) by +16.22 pts; runs AA suite at $2.11/task vs. Opus 5.5's $5.98/task.

1. Composite Frontier Position & Cost-Efficiency Pareto

Kimi K3.1 Pro leaps +11.50 points over Kimi K3 (43.59 → 55.09) on the independent Artificial Analysis Intelligence Index v4.3.2, trailing only Claude Opus 5.5 (57.62), Claude Sonnet 5.5 (56.00), and Meta's API-restricted Muse Wonder Full (55.80).

Figure 1: Composite Frontier and Cost Pareto

2. Historical Trajectory & Implied Time-Lag (2024 – October 2026)

Measuring the horizontal time lag across 626 models on AA v4.3.2 and 249 models on Epoch ECI shows why index composition governs the headline lag estimate (1.0 month on agentic-heavy AA vs. ~4.5 months on science/math-heavy ECI).

Figure 2: Historical Trajectory and Time Lag

3. The Bifurcated Capability Profile: Independent AA Evaluations & Enterprise Work

China has reached frontier parity in general agentic coding, long-context retrieval, and document reasoning, while Western frontier models retain an 8-to-30 point lead in scientific research workflows, research physics, and tail-knowledge reliability.

4. Auditing Moonshot's 41-Benchmark Launch Suite (Vendor Table vs. Omitted Western SOTA)

Against the 3 Western models printed in Moonshot's release table (Opus 5.5, Fable 5.1, GPT-6 Astra), Kimi K3.1 Pro leads or ties on 16 of 41 benchmarks. Adding omitted Western SOTA models (Claude Sonnet 5.5, Gemini 4 Argon, Muse Wonder Full) reduces K3.1 Pro's leads/ties to 13 of 41.

5. Cross-Leaderboard Reality Check: 9 Major Public AI Leaderboards

Across 9 independent public leaderboards, Western models hold #1 on every board, while Kimi K3.1 Pro breaks into the global Top 4–9 on AA (#4), LMArena WebDev (#8), Vals Enterprise Index (#8), and LiveBench 2.0 (#9).

Figure 5: Nine Public Leaderboards Matrix

Interactive Benchmark Explorer (All 41 Comparable Launch Benchmarks)

Filter by capability domain to inspect Kimi K3.1 Pro's score, the best printed Western model, and the adjusted gap when omitted Western SOTA models are included.