Who ranks #1 on the Refspatialbench leaderboard?
As of August 20, 2026, Qwen3.6-27B by Qwen ranks #1 on Refspatialbench at 70%. API pricing is $0.60/M input and $3.60/M output.
Refspatialbench
🏆 LeaderboardAs of August 20, 2026, Qwen3.6-27B is #1 for Refspatialbench at 70%. Ranked by the Refspatialbench score 6 models in this index have a published Refspatialbench score. Refspatialbench leaderboard: rank models by Refspatialbench next to live API token prices.
Updated August 20, 2026282 models33 providers
Showing 1–50 of 282 models
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The index
All Large Language Models
282 models across 33 providers. Search or jump to a lab — every model page stays linked here.
OpenAI
51 modelsGPT-5.6 CyberGPT-5.6 LunaGPT-5.6 SolGPT-5.6 TerraGPT-5.5 InstantGPT-5.5GPT-5.5 ProGPT-5.4 miniGPT-5.4 nanoGPT-5.4GPT-5.3 ChatGPT-5.3 CodexGPT-5.2 CodexGPT-5.2GPT-5.2 ProGPT-5.1 CodexGPT-5.1GPT-5.1 Codex HighGPT-5.1 Codex MiniGPT-5.1 HighGPT-5.1 InstantGPT-5.1 MediumGPT-5.1 ThinkingGPT-5 CodexGPT-5GPT-5 HighGPT-5 MediumGPT-5 miniGPT-5 nanoGPT OSS 120BGPT OSS 120B HighGPT OSS 20BGPT OSS 20B Higho3-proo3o4-miniGPT-4.1GPT-4.1 miniGPT-4.1 nanoo3-minio1o1-proo1-minio1-previewGPT-4oGPT-4o miniChatGPT-4o LatestGPT-4oGPT-4 TurboGPT-4GPT-3.5 Turbo
Anthropic
22 modelsClaude Opus 5Claude Sonnet 5Claude Fable 5Claude Mythos 5Claude Opus 4.8Claude Opus 4.7Claude Sonnet 4.6Claude Opus 4.6Claude Opus 4.5Claude Haiku 4.5Claude Sonnet 4.5Claude Opus 4.1Claude Opus 4Claude Sonnet 4Claude 3.7 SonnetClaude 3.5 HaikuClaude 3.5 SonnetClaude 3.5 SonnetClaude 3 HaikuClaude 3 OpusClaude 3 SonnetClaude Mythos Preview
Gemini 3.7 FlashGemini 3.5 Flash-LiteGemini 3.6 FlashGemini 3.5 FlashGemma 4 26B-A4BGemma 4 31BGemini 3.1 Flash-LiteGemini 3.1 ProGemini 3 FlashGemini 3 ProGemma 3n E4B InstructedGemini 2.5 Flash-LiteGemini 2.5 Pro Preview 06-05Gemini 2.5 FlashGemini 2.5 ProGemma 3 12BGemma 3 27BGemma 3 4BGemini 2.0 Flash-LiteGemini 2.0 FlashGemma 2 27BGemini 1.5 FlashGemini 1.5 ProGemini 1.5 Flash 8BGemini 1.0 Pro
Cursor
2 models
xAI
15 models
DeepSeek
16 models
Qwen
38 modelsQwen3.8-27BQwen3.8-2.4T-A95BQwen3.8 MaxQwen3.7 FlashQwen3.7-PlusQwen3.7 MaxQwen3.6-27BQwen3.6-35B-A3BQwen3.6 PlusQwen3.5-9BQwen3.5-122B-A10BQwen3.5-27BQwen3.5-35B-A3BQwen3.5-397B-A17BQwen3 MaxQwen3 VL 235B A22B InstructQwen3 VL 235B A22B ThinkingQwen3 VL 30B A3B InstructQwen3 VL 30B A3B ThinkingQwen3 VL 32B InstructQwen3 VL 4B InstructQwen3 VL 4B ThinkingQwen3 VL 8B InstructQwen3 VL 8B ThinkingQwen3-Next-80B-A3B-InstructQwen3-Next-80B-A3B-ThinkingQwen3-235B-A22B-Thinking-2507Qwen3-235B-A22B-Instruct-2507Qwen3 235B A22BQwen3 30B A3BQwen3 32BQwen3-Coder 480B A35B InstructQwen2.5 VL 72B InstructQwen3-CoderQwQ-32B-PreviewQwen2.5 72B InstructQwen2.5 7B InstructQwen2.5-Coder 32B Instruct
AI21 Labs
2 models
Amazon
5 models
Baidu
1 models
ByteDance
2 models
Cohere
3 models
IBM
1 models
Inception
1 models
inclusionAI
1 models
LG AI Research
1 models
Meituan
4 models
Meta
12 models
Mistral
23 modelsMistral Medium 3.5Mistral Small 4Min istral 3 (3B Reasoning 2512)MiniStral 3 (14B Instruct 2512)Ministral 3 (14B Reasoning 2512)Ministral 3 (3B Instruct 2512)Ministral 3 (8B Instruct 2512)Ministral 3 (8B Reasoning 2512)Mistral Large 3 (675B Instruct 2512)Mistral Large 3Devstral Small 1.1Devstral MediumMistral Small 3.2 24B InstructMagistral MediumMistral Small 3.1 24B BaseMistral Small 3.1 24B InstructMistral Small 3 24B InstructPixtral LargeMinistral 8B InstructMistral SmallPixtral-12BMistral Large 2Mistral NeMo Instruct
Moonshot AI
9 models
Nous Research
1 models
NVIDIA
5 models
Poolside
2 models
Sakana AI
1 models
StepFun
1 models
Tencent
1 models
Thinking Machines
1 models
Unisound
1 models
Upstage
1 models
Xiaomi
3 modelsWhich model leads Refspatialbench right now?
As of August 20, 2026, Qwen3.6-27B by Qwen is #1 for Refspatialbench at 70%. Ranked by the Refspatialbench score This board also tracks Refspatialbench. Next on the same board: Qwen3 VL 235B A22B Thinking and Qwen3.5-122B-A10B. This refspatialbench leaderboard ranks models by Refspatialbench. Scores come from public evals. Prices are the live API rates in the table above.
Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); Anthropic Claude API pricing (https://platform.claude.com/docs/en/about-claude/pricing); Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing)
| Rank | Model | Refspatialbench | Input /M | Output /M |
|---|---|---|---|---|
| 1 | Qwen3.6-27B | 70% | $0.60 | $3.60 |
| 2 | Qwen3 VL 235B A22B Thinking | 69.9% | $0.45 | $3.49 |
| 3 | Qwen3.5-122B-A10B | 69.3% | $0.40 | $3.20 |
| 4 | Qwen3.5-27B | 67.7% | $0.30 | $2.40 |
| 5 | Qwen3.6-35B-A3B | 64.3% | $0.14 | $1.00 |
| 6 | Qwen3.5-35B-A3B | 63.5% | $0.25 | $2.00 |
Related LLM leaderboards
Individual benchmark pages
Rank one eval at a time. All LLM benchmarks.
Refspatialbench FAQ
What are the top models on Refspatialbench?
The current Refspatialbench ranking as of August 20, 2026 is 1. Qwen3.6-27B at 70%; 2. Qwen3 VL 235B A22B Thinking at 69.9%; 3. Qwen3.5-122B-A10B at 69.3%.
Which refspatialbench model is the cheapest?
Qwen3.6-35B-A3B is the cheapest scored model on this refspatialbench leaderboard at $0.14/M input and $1.00/M output ($1.14 blended). Qwen3.6-27B still leads Refspatialbench at 70%.
Should I always pick the #1 Refspatialbench model?
Not automatically. Qwen3.6-27B leads Refspatialbench, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Refspatialbench against input/output price, context window, and related evals.
How often is the Refspatialbench leaderboard updated?
Scores and API prices on this page are refreshed from published evals and provider rates. The snapshot is labeled August 20, 2026. Treat it as a current index, not a one-off blog post.
What is Refspatialbench?
Refspatialbench is a public LLM eval (the Refspatialbench score). This page ranks models that have published a score, next to live API prices.
Where is the Refspatialbench leaderboard?
This page is the Refspatialbench leaderboard. Models are sorted by Refspatialbench, with input and output token prices on the same row so you can weigh score against cost. Official boards often omit price; that comparison is the point of this index.
How is this Refspatialbench ranking different from the official board?
Official eval pages own the methodology. This page keeps the published Refspatialbench score next to live API $/M so you can pick a production SKU, not only a trophy number.