SRCH:05856138
Open LLM leaderboard evaluation results Llama Mistral Qwen DeepSeek benchmark scores comparison
Abstract
Abstract: Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and generation is acquired by training billions of model's parameters on massive amounts of text data, as predicted by scaling laws cite\kaplan2020scaling,hoffmann2022training\. The research area of LLMs, while very recent, is evolving rapidly in many different ways. In this paper, we review some of the most prominent LLMs, including three popular LLM families
Research Question
Open LLM leaderboard evaluation results Llama Mistral Qwen DeepSeek benchmark scores comparison
Verification Level
| Paper level | L2, Source-grounded claims | |
| Source-grounded claims | 10 | |
| Claim record source | not publicly specified |
Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.
Quality Tier
| Tier | Flagship candidate | |
| Basis | Review score, verified-claim count, and public artifact coverage meet flagship-candidate thresholds. |
Descriptive public triage only; this tier does not alter current publication or DOI behavior.
Quality Dimensions
| Evidence strength | MEDIUM | |
| Citation grounding | MEDIUM | |
| Uncertainty disclosure | MEDIUM | |
| Reproducibility status | HIGH |
Automated triage signals derived from public fields; not human peer review or independent validation.
Correction Record
| Status | CURRENT |
| Correction count | 0 |
| Manifest contract | paper-manifest-v1.1 |
| Correction contract | correction-record-v1 |
Public corrections are additive records. Current status does not claim the synthesis is error-free.
Provenance
| Publisher | Assignee Research |
| Public provenance | L4, External archival record |
| Report artifact | Available |
| External record | Registered |
| Claim lineage | 10 aggregate source-grounded claims |
| Review method | Automated multi-reviewer assessment |
| Quality guide | How to read scores, claims, manifests, and evidence links |
| Provenance contract | source-provenance-v1 |
| Note | Machine-generated synthesis of existing literature. Not primary research. |