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Scale Labs MultiNRC (MultiNRC)

We show this table for reference; we do not rank on it.

A Scale Labs public leaderboard mirrored as display-only reference data. It does not affect BenchLM rankings.

Scale score on MultiNRC — November 12, 2026 snapshot

We mirror the published scale score view for MultiNRC. Muse Spark 1.1 leads the public snapshot at 65.6%, followed by gpt-5-pro-2025-10-06 (65.2%) and gemini-3.1-pro-preview (64.7%). We do not use these results to rank models overall.

1Closed

Muse Spark 1.1

Meta

65.6%
Overall 63.49Context 1M
2

gpt-5-pro-2025-10-06

OpenAI

65.2%
3

gemini-3.1-pro-preview

Google

64.7%

44 modelsKnowledgeCurrentDisplay onlyUpdated November 12, 2026 snapshot

Scale score table (44 models)

Scale score results for MultiNRC
RankModel / configurationScoreParameters (B)Open / closed
1Muse Spark 1.1Meta
65.6%
Not reportedClosed
2gpt-5-pro-2025-10-06OpenAI
65.2%
Not reportedUnknown
3gemini-3.1-pro-previewGoogle
64.7%
Not reportedUnknown
4GPT-5.4 ProOpenAI
62.3%
Not reportedClosed
5Muse SparkMeta
59.0%
Not reportedClosed
6gemini-3-pro-previewGoogle
59.0%
Not reportedUnknown
7gpt-5.4-2026-03-05 (xhigh thinking)OpenAI
58.3%
Not reportedUnknown
8claude-opus-4-6-thinking-maxAnthropic
57.1%
Not reportedUnknown
9gpt-5-2025-08-07OpenAI
52.1%
Not reportedUnknown
10gpt-5.1-thinkingOpenAI
49%
Not reportedUnknown
11o3-pro-2025-06-10-highOpenAI
49%
Not reportedUnknown
12Claude Opus 4.5 ThinkingAnthropic
48.6%
Not reportedClosed
13claude-opus-4-6 (Non-Thinking)Anthropic
48.3%
Not reportedUnknown
14o3-2025-04-16-highOpenAI
45.5%
Not reportedUnknown
15Gemini-2.5-Pro-Preview-06-05Google
45.1%
Not reportedUnknown
16o3-2025-04-16-mediumOpenAI
44.5%
Not reportedUnknown
17GPT-5.2OpenAI
42.2%
Not reportedClosed
18Claude Opus 4.5Anthropic
41.2%
Not reportedClosed
19claude-opus-4-1-20250805-thinkingAnthropic
38.4%
Not reportedUnknown
20Claude Sonnet 4.5 ThinkingAnthropic
35.8%
Not reportedClosed
21Kimi K2.5Moonshot AI
35.2%
Not reportedOpen
22Claude 4 Opus ThinkingAnthropic
33.9%
Not reportedClosed
23claude-opus-4-1-20250805Anthropic
29.7%
Not reportedUnknown
24Claude 4 OpusAnthropic
29%
Not reportedClosed
25Claude Sonnet 4.5Anthropic
28.1%
Not reportedClosed
26Claude 3.7 Sonnet ThinkingAnthropic
27.8%
Not reportedClosed
27DeepSeek-R1-0528DeepSeek
27.6%
Not reportedOpen
28Qwen3-235B-A22B-Thinking-2507Alibaba
27.1%
Not reportedUnknown
29gemini-3.1-flash-lite-previewGoogle
25.0%
Not reportedUnknown
30DeepSeek-R1DeepSeek
24.3%
Not reportedOpen
31GPT-5 miniOpenAI
23.9%
Not reportedClosed
32DeepSeek V3.1DeepSeek
23.6%
Not reportedOpen
33o4-mini (high)OpenAI
22.2%
Not reportedClosed
34GPT-4.1OpenAI
21.2%
Not reportedClosed
35kimi-k2-instructMoonshot AI
18.5%
Not reportedUnknown
36Claude 4 SonnetAnthropic
18.4%
Not reportedClosed
37gpt-5.1-instantOpenAI
18.3%
Not reportedUnknown
38Qwen3 235B-A22BAlibaba
17.6%
Not reportedOpen
39glm-4p5Z.AI
17.4%
Not reportedUnknown
40GPT-OSS 120BOpenAI
15.2%
Not reportedOpen
41GPT-4oOpenAI
12.4%
Not reportedClosed
42GPT-OSS 20BOpenAI
10.4%
Not reportedOpen
43glm-4p5-airZ.AI
10.4%
Not reportedUnknown
44Llama 4 MaverickMeta
8.4%
Not reportedOpen

How to read this leaderboard

Compare the published configurations as complete evaluation systems. The source can combine a base model, agent scaffold, tools, budget, and inference setting in each result.

Operator receipt: 44 sourced rows are currently displayable on this page; the leading published row is Muse Spark 1.1 at 65.6%.

Honest limit: This Scale table is display-only context, not benchmark provenance or a weighted model-only comparison.

MultiNRC on Scale Labs

How BenchLM shows MultiNRC

BenchLM mirrors 44 published rows from Scale Labs’ public MultiNRC leaderboard, captured on November 12, 2026 snapshot.

The table is display only. It is useful context for a published agent or model configuration, but it does not enter BenchLM’s overall or category rankings.

Snapshot

44 published rowsScale Labs sourceDisplay only
MultiNRC on Scale Labs

The published MultiNRC snapshot places Muse Spark 1.1 first at 65.6%. The third row is 0.9 points behind. The broader top-10 range is 16.6 points, so the table still separates the published systems.

44 models have been evaluated on MultiNRC. The benchmark falls in the Knowledge category. We keep external benchmark mirrors separate from the weighted global scoring system, so these results remain source-specific evidence. MultiNRC is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.

About MultiNRC

Year

2026

Tasks

44 published rows

Format

Published Scale leaderboard score

Difficulty

External agent and model evaluation

BenchLM mirrors 44 published rows from the MultiNRC public table captured on November 12, 2026 snapshot.

Scale Labs leaderboardPublic benchmark source

Freshness and provenance

Version

MultiNRC 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.

Questions

What does MultiNRC measure?

A Scale Labs public leaderboard mirrored as display-only reference data. It does not affect BenchLM rankings.

Which model leads the published MultiNRC snapshot?

Muse Spark 1.1 currently leads the published MultiNRC snapshot with 65.6% scale score. BenchLM shows this benchmark for display only and does not use it in overall rankings.

How many models are evaluated on MultiNRC?

The November 12, 2026 snapshot snapshot contains 44 AI models.

Last updated: November 12, 2026 snapshot · mirrored from the public benchmark leaderboard

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