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Alibaba Cloud / Qwen Team · proprietary
Qwen3.6 Plus
Qwen3.6 Plus by Alibaba Cloud / Qwen Team appears in 2 sources with Reasoning at 52.14. Best read for Coding, High intelligence, LLM.
CreatorAlibaba Cloud / Qwen Team
Release date2026-03-31
Knowledge cutoffNot published
Context1M tokens
Input price$0.5/M tokens
Output price$3/M tokens
Modalitytext + vision
CountryCN
Metrics
All source-backed metrics
LLM Stats Rank26ranking · source_rank
Reasoning52.14reasoning · index_reasoning
Math48.96math · index_math
Coding41.7coding · index_code
Research25.09research · index_search
Vision35.08multimodal · index_vision
Tool calling29.2tool_calling · index_tool_calling
Long context37.21long_context · index_long_context
Finance54.2domain · index_finance
Legal54.23domain · index_legal
Healthcare52.74domain · index_healthcare
GPQA90.4 %reasoning · gpqa_score
SWE-bench Verified78.8 %coding · swe_bench_verified_score
Code Arena1,211.03 %coding · coding_arena_score
Humanity Last Exam28.8 %reasoning · hle_score
MMMLU89.5 %reasoning · mmmlu_score
MMMU86 %multimodal · mmmu_score
MMMU-Pro78.8 %multimodal · mmmu_pro_score
Toolathlon39.8 %tool_calling · toolathlon_score
MCP Atlas74.1 %tool_calling · mcp_atlas_score
SWE-bench Pro56.6 %coding · swe_bench_pro_score
CharXiv-R81.5 %multimodal · charxiv_r_score
ScreenSpot Pro68.2 %multimodal · screenspot_pro_score
Context1,000,000 tokenscontext · context
Speed117.36 c/sperformance · throughput
Latency43,612.92 msperformance · latency
Input price0.5 $/Mpricing · input_price
Output price3 $/Mpricing · output_price
Arena Rating1,439.89metric
Arena Rank39metric
Vote Count10,531metric
Evidence
Citations and source overlap
FAQ
How should I read this profile?
Treat this as a source-backed model dossier, not an EvalKit-run verification. The public values are replicated from linked sources and kept source-scoped.
Is Qwen3.6 Plus verified by EvalKit?
No. EvalKit currently shows 0 verified rows until real run evidence exists.
Why can metrics disagree?
Different sources test different tasks, dates, prompts, and aggregation methods. EvalKit keeps those differences visible instead of merging them into a fake universal score.