APEX-1 — Mercor evaluation (APEX-1 (Mercor))
We show this table for reference; we do not rank on it.
Single-turn professional deliverables graded against expert-written criteria. This table shows Mercor-run configurations for reference and is excluded from model rankings.
Evaluation results published by Mercor. Published evaluation aggregates only; task contents and dataset license grants are not included.
Mean Score on APEX-1 (Mercor) — October 15, 2026 capture
We mirror the published mean score view for APEX-1 (Mercor). Muse Spark 1.2 leads the public snapshot at 75.60%, followed by Muse Spark 1.3 (74.00%) and Fable 5.1 (73.80%). We do not use these results to rank models overall.
Muse Spark 1.2
Meta
Single-shot agent · xhigh reasoning
Published margin ±2.3 · 1,593 reported samples
Muse Spark 1.3
Meta
Single-shot agent · xhigh reasoning
Published margin ±2.3 · 1,599 reported samples
Fable 5.1
Anthropic
Single-shot agent · max reasoning
Published margin ±2.7 · 1,577 reported samples
70 configurationsCross-domainDated Mercor configurationsDisplay onlyUpdated October 15, 2026 capture
Mean Score table (70 configurations)
| Rank | Model / configuration | Score | Parameters (B) | Open / closed |
|---|---|---|---|---|
| 1 | Muse Spark 1.2MetaSingle-shot agent · xhigh reasoningPublished margin ±2.3 · 1,593 reported samples | 75.60% | Not reported | Unknown |
| 2 | Muse Spark 1.3MetaSingle-shot agent · xhigh reasoningPublished margin ±2.3 · 1,599 reported samples | 74.00% | Not reported | Unknown |
| 3 | Fable 5.1AnthropicSingle-shot agent · max reasoningPublished margin ±2.7 · 1,577 reported samples | 73.80% | Not reported | Unknown |
| 4 | Muse Spark 1.1MetaSingle-shot agent · xhigh reasoningPublished margin ±2.2 · 1,591 reported samples | 73.80% | Not reported | Unknown |
| 5 | GPT-5.6 Sol (Pro)OpenAISingle-shot agent · max reasoningPublished margin ±2.4 · 1,600 reported samples | 73.10% | Not reported | Unknown |
| 6 | Muse Spark 1.3MetaSingle-shot agent · max reasoningPublished margin ±2.3 · 1,600 reported samples | 73.00% | Not reported | Unknown |
| 7 | GPT-5.6 TerraOpenAISingle-shot agent · max reasoningPublished margin ±2.4 · 1,598 reported samples | 69.50% | Not reported | Unknown |
| 8 | GPT-6 AstraOpenAISingle-shot agent · xhigh reasoningPublished margin ±2.6 · 1,580 reported samples | 69.30% | Not reported | Unknown |
| 9 | GPT-6.1 SolOpenAISingle-shot agent · max reasoningPublished margin ±2.6 · 1,436 reported samples | 69.30% | Not reported | Unknown |
| 10 | Gemini 3.8 FlashGoogleSingle-shot agent · high reasoningPublished margin ±2.7 · 1,599 reported samples | 68.80% | Not reported | Unknown |
| 11 | Opus 5AnthropicSingle-shot agent · xhigh reasoningPublished margin ±2.9 · 1,595 reported samples | 68.60% | Not reported | Unknown |
| 12 | Kimi K3KimiSingle-shot agent · max reasoningPublished margin ±2.3 · 1,600 reported samples | 68.40% | Not reported | Unknown |
| 13 | GPT-5.5OpenAISingle-shot agent · xhigh reasoningPublished margin ±2.4 · 1,600 reported samples | 68.40% | Not reported | Unknown |
| 14 | Grok 4.6xAISingle-shot agent · xhigh reasoningPublished margin ±2.5 · 1,600 reported samples | 67.70% | Not reported | Unknown |
| 15 | GPT 5.4OpenAISingle-shot agent · high reasoningPublished margin ±2.4 · 3,142 reported samples | 67.20% | Not reported | Unknown |
| 16 | Gemini 3.7 FlashGoogleSingle-shot agent · high reasoningPublished margin ±2.6 · 1,600 reported samples | 67.00% | Not reported | Unknown |
| 17 | GPT-5.6 LunaOpenAISingle-shot agent · max reasoningPublished margin ±2.5 · 1,586 reported samples | 66.60% | Not reported | Unknown |
| 18 | Fable 5AnthropicSingle-shot agent · max reasoningPublished margin ±2.9 · 1,600 reported samples | 66.00% | Not reported | Unknown |
| 19 | Gemini 3.6 FlashGoogleSingle-shot agent · high reasoningPublished margin ±2.5 · 1,600 reported samples | 66.00% | Not reported | Unknown |
| 20 | DeepSeek-V4-Pro-0813DeepSeekSingle-shot agent · max reasoningPublished margin ±2.5 · 1,591 reported samples | 66.00% | Not reported | Unknown |
| 21 | Opus 5.5AnthropicSingle-shot agent · max reasoningPublished margin ±3.2 · 1,600 reported samples | 65.80% | Not reported | Unknown |
| 22 | Opus 4.6AnthropicSingle-shot agent · max reasoningPublished margin ±2.6 · 1,600 reported samples | 65.70% | Not reported | Unknown |
| 23 | GPT-5.4OpenAISingle-shot agent · xhigh reasoningPublished margin ±2.4 · 1,600 reported samples | 65.60% | Not reported | Unknown |
| 24 | DeepSeek-V4.1-FlashDeepSeekSingle-shot agent · max reasoningPublished margin ±2.6 · 1,600 reported samples | 65.50% | Not reported | Unknown |
| 25 | Grok 4.7xAISingle-shot agent · xhigh reasoningPublished margin ±2.6 · 1,591 reported samples | 65.40% | Not reported | Unknown |
| 26 | Opus 4.6AnthropicSingle-shot agent · high reasoningPublished margin ±2.7 · 1,599 reported samples | 65.30% | Not reported | Unknown |
| 27 | GPT-5.2-CodexOpenAISingle-shot agent · high reasoningPublished margin ±2.6 · 1,588 reported samples | 65.30% | Not reported | Unknown |
| 28 | Qwen3.8-MaxAlibabaSingle-shot agent · xhigh reasoningPublished margin ±2.5 · 1,559 reported samples | 65.30% | Not reported | Unknown |
| 29 | GPT-5.2OpenAISingle-shot agent · high reasoningPublished margin ±2.5 · 1,599 reported samples | 64.70% | Not reported | Unknown |
| 30 | Haiku 5.5AnthropicSingle-shot agent · max reasoningPublished margin ±2.6 · 1,600 reported samples | 64.70% | Not reported | Unknown |
| 31 | GPT-5.3-CodexOpenAISingle-shot agent · high reasoningPublished margin ±2.4 · 1,599 reported samples | 64.60% | Not reported | Unknown |
| 32 | GPT-5OpenAISingle-shot agent · high reasoningPublished margin ±2.5 · 3,182 reported samples | 64.50% | Not reported | Unknown |
| 33 | DeepSeek-V4-FlashDeepSeekSingle-shot agent · max reasoningPublished margin ±2.6 · 1,600 reported samples | 63.80% | Not reported | Unknown |
| 34 | GPT-6 SolOpenAISingle-shot agent · max reasoningPublished margin ±2.6 · 1,588 reported samples | 63.60% | Not reported | Unknown |
| 35 | GLM-5.3ZhipuSingle-shot agent · max reasoningPublished margin ±2.9 · 1,593 reported samples | 62.90% | Not reported | Unknown |
| 36 | GPT-5-CodexOpenAISingle-shot agent · high reasoningPublished margin ±2.6 · 1,593 reported samples | 62.80% | Not reported | Unknown |
| 37 | Opus 4.8AnthropicSingle-shot agent · max reasoningPublished margin ±3 · 1,600 reported samples | 62.70% | Not reported | Unknown |
| 38 | Qwen 3.8 27BAlibabaSingle-shot agent · xhigh reasoningPublished margin ±2.7 · 1,580 reported samples | 62.60% | Not reported | Unknown |
| 39 | Opus 4.7AnthropicSingle-shot agent · max reasoningPublished margin ±2.8 · 1,600 reported samples | 62.20% | Not reported | Unknown |
| 40 | Gemini 3.5 FlashGoogleSingle-shot agent · high reasoningPublished margin ±2.8 · 1,600 reported samples | 62.20% | Not reported | Unknown |
| 41 | GPT-6 LunaOpenAISingle-shot agent · max reasoningPublished margin ±2.7 · 1,600 reported samples | 62.00% | Not reported | Unknown |
| 42 | GPT-5.1-CodexOpenAISingle-shot agent · high reasoningPublished margin ±2.7 · 1,591 reported samples | 61.90% | Not reported | Unknown |
| 43 | Gemini 3.1 ProGoogleSingle-shot agent · high reasoningPublished margin ±2.5 · 1,599 reported samples | 61.80% | Not reported | Unknown |
| 44 | Grok 4.5xAISingle-shot agent · high reasoningPublished margin ±2.5 · 1,600 reported samples | 61.80% | Not reported | Unknown |
| 45 | GLM-5.2ZhipuSingle-shot agent · max reasoningPublished margin ±2.5 · 1,600 reported samples | 61.50% | Not reported | Unknown |
| 46 | Gemini 3 ProGoogleSingle-shot agent · high reasoningPublished margin ±2.4 · 3,200 reported samples | 60.90% | Not reported | Unknown |
| 47 | Gemini 3 FlashGoogleSingle-shot agent · high reasoningPublished margin ±2.3 · 1,600 reported samples | 60.90% | Not reported | Unknown |
| 48 | o3OpenAISingle-shot agent · high reasoningPublished margin ±2.5 · 1,598 reported samples | 60.50% | Not reported | Unknown |
| 49 | Kimi K2.7 CodeKimiSingle-shot agent · high reasoningPublished margin ±2.5 · 1,596 reported samples | 60.10% | Not reported | Unknown |
| 50 | MiniMax-M3MiniMaxSingle-shot agent · high reasoningPublished margin ±2.5 · 1,600 reported samples | 59.80% | Not reported | Unknown |
| 51 | DeepSeek-V4-ProDeepSeekSingle-shot agent · max reasoningPublished margin ±2.7 · 1,594 reported samples | 59.70% | Not reported | Unknown |
| 52 | GLM-5.3-FlashZhipuSingle-shot agent · max reasoningPublished margin ±3.1 · 1,600 reported samples | 58.70% | Not reported | Unknown |
| 53 | InklingThinking MachinesSingle-shot agent · high reasoningPublished margin ±2.7 · 1,596 reported samples | 58.10% | Not reported | Unknown |
| 54 | Grok 4.1xAISingle-shot agent · fast reasoningPublished margin ±2.6 · 1,600 reported samples | 57.50% | Not reported | Unknown |
| 55 | Opus 4.5AnthropicSingle-shot agent · high reasoningPublished margin ±2.8 · 3,199 reported samples | 57.30% | Not reported | Unknown |
| 56 | Grok 4xAISingle-shot agentPublished margin ±2.7 · 1,592 reported samples | 57.10% | Not reported | Unknown |
| 57 | Nemotron 3 UltraNVIDIASingle-shot agent · high reasoningPublished margin ±2.6 · 1,600 reported samples | 56.10% | Not reported | Unknown |
| 58 | Sonnet 4.6AnthropicSingle-shot agent · high reasoningPublished margin ±3.3 · 1,600 reported samples | 55.10% | Not reported | Unknown |
| 59 | Gemini 3.5 Flash LiteGoogleSingle-shot agent · high reasoningPublished margin ±2.5 · 1,600 reported samples | 54.70% | Not reported | Unknown |
| 60 | Sonnet 5.5AnthropicSingle-shot agent · max reasoningPublished margin ±3.7 · 1,598 reported samples | 53.90% | Not reported | Unknown |
| 61 | Kimi K2 (Thinking)KimiSingle-shot agent · high reasoningPublished margin ±2.5 · 1,517 reported samples | 52.40% | Not reported | Unknown |
| 62 | GLM-5.1ZhipuSingle-shot agentPublished margin ±2.5 · 1,576 reported samples | 52.40% | Not reported | Unknown |
| 63 | GLM-4.7ZhipuSingle-shot agentPublished margin ±2.7 · 1,439 reported samples | 51.70% | Not reported | Unknown |
| 64 | DeepSeek-V3.2DeepSeekSingle-shot agentPublished margin ±2.7 · 1,599 reported samples | 51.50% | Not reported | Unknown |
| 65 | Qwen3.5AlibabaSingle-shot agentPublished margin ±2.5 · 1,600 reported samples | 50.30% | Not reported | Unknown |
| 66 | Sonnet 5AnthropicSingle-shot agent · max reasoningPublished margin ±3.4 · 1,599 reported samples | 49.60% | Not reported | Unknown |
| 67 | GLM-5 (Thinking)ZhipuSingle-shot agentPublished margin ±2.9 · 1,599 reported samples | 49.00% | Not reported | Unknown |
| 68 | Gemma 4 31BGoogleSingle-shot agentPublished margin ±2.7 · 1,574 reported samples | 48.10% | Not reported | Unknown |
| 69 | GPT-OSS-120BOpenAISingle-shot agent · high reasoningPublished margin ±2.7 · 1,600 reported samples | 46.40% | Not reported | Unknown |
| 70 | MiniMax-M2.7MiniMaxSingle-shot agent · high reasoningPublished margin ±2.7 · 1,600 reported samples | 45.80% | Not reported | Unknown |
How to read this Mercor evaluation
We captured Mercor's APEX-1 results on October 15, 2026. The table preserves 70 published configurations, their source identifiers, reasoning settings, and disclosed mean score values. These are results from Mercor's evaluation setup; we did not rerun them.
This dated source table is display only and does not enter overall or category rankings. Source configurations retain their external identity, including Pro descriptors and different effort settings.
Mean score is rubric-criterion coverage, not the fraction of tasks fully completed. The leaderboard description lists 400 tasks and eight runs, while the general methodology lists 300 tasks and four runs. We preserve the published aggregates and sample counts without choosing a common denominator or combining these results with another APEX edition.
The row labels retain published error margins and sample counts when supplied. Missing margins and counts remain unreported; a sample count is not used to reconstruct a task denominator. Except where the dedicated source defines an interval, the confidence level is unreported. Equal displayed scores and overlapping margins do not establish statistical ties. Capture time does not establish individual evaluation dates.
The general methodology lists expert-authored rubrics, scored criterion by criterion and a judge of LLM judge over expert rubrics. Its run-count label is k = 4. The linked result page takes precedence where its setup differs, as noted above.
Snapshot
The published APEX-1 (Mercor) snapshot places Muse Spark 1.2 first at 75.60%. The third row is 1.80 points behind. The broader top-10 range is 6.80 points, so many of the published results sit in a relatively narrow band.
70 configurations are shown for APEX-1 (Mercor). The benchmark falls in the Cross-domain category. We keep external benchmark mirrors separate from the weighted global scoring system, so these results remain source-specific evidence. APEX-1 (Mercor) is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About APEX-1 (Mercor)
Tasks
Task and run counts differ across source pages
Format
Mean Score
Difficulty
Source-specific evaluation
The selected headline is Mean Score. Source model identifiers, effort settings, published margins, and reported sample counts remain attached to the source configuration. Public-set results and Mercor task extensions occupy separate tables.
Freshness and provenance
Version
APEX-1; Mercor Mean Score; singleshot_agent
Refresh cadence
Reviewed dated source capture
Staleness state
Dated Mercor configurations
Question availability
Upstream task access and terms; only aggregate results mirrored
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 APEX-1 (Mercor) measure?
Single-turn professional deliverables graded against expert-written criteria. This table shows Mercor-run configurations for reference and is excluded from model rankings.
Which model leads the published APEX-1 (Mercor) snapshot?
Muse Spark 1.2 currently leads the published APEX-1 (Mercor) snapshot with 75.60% mean score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on APEX-1 (Mercor)?
The October 15, 2026 capture snapshot contains 70 source configurations.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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