Mega Xcopa

🏆 Leaderboard

As of August 31, 2026, Phi-3.5-MoE-instruct is #1 for Mega Xcopa at 76.6%. Ranked by the Mega Xcopa score 2 models in this index have a published Mega Xcopa score. Mega Xcopa leaderboard: rank models by Mega Xcopa next to live API token prices.

Updated August 31, 2026345 models36 providers


Phi-3.5-MoE-instructOSS Microsoft · Open Source	76.6%	$0.21
Phi-3.5-mini-instructOSS Microsoft · Open Source	63.1%	$0.20
ChatGPT-4o Latest OpenAI · Proprietary	—	$12.50
Claude 3 Haiku Anthropic · Proprietary	—	$1.50
Claude 3 Opus Anthropic · Proprietary	—	$90.00
Claude 3 Sonnet Anthropic · Proprietary	—	$18.00
Claude 3.5 Haiku Anthropic · Proprietary	—	$4.80
Claude 3.5 Sonnet Anthropic · Proprietary	—	$18.00
Claude 3.5 Sonnet Anthropic · Proprietary	—	$18.00
Claude 3.7 Sonnet Anthropic · Proprietary	—	$18.00
Claude Fable 5 Anthropic · Proprietary	—	$60.00
Claude Haiku 4.5 Anthropic · Proprietary	—	$6.00
Claude Mythos 5 Anthropic · Proprietary	—	$60.00
Claude Mythos Preview Anthropic · Proprietary	—	$60.00
Claude Opus 4 Anthropic · Proprietary	—	$90.00
Claude Opus 4.1 Anthropic · Proprietary	—	$90.00
Claude Opus 4.5 Anthropic · Proprietary	—	$30.00
Claude Opus 4.6 Anthropic · Proprietary	—	$30.00
Claude Opus 4.7 Anthropic · Proprietary	—	$30.00
Claude Opus 4.8 Anthropic · Proprietary	—	$30.00
Claude Opus 5 Anthropic · Proprietary	—	$30.00
Claude Sonnet 4 Anthropic · Proprietary	—	$18.00
Claude Sonnet 4.5 Anthropic · Proprietary	—	$18.00
Claude Sonnet 4.6 Anthropic · Proprietary	—	$18.00
Claude Sonnet 5 Anthropic · Proprietary	—	$12.00
Codestral-22BOSS Mistral · Open Source · via Mistral AI	—	$1.20
Command A+OSS Cohere · Open Source	—	$12.50
Command R+OSS Cohere · Open Source	—	$1.25
Composer 2 Cursor · Proprietary	—	$3.00
Composer 2 Fast Cursor · Proprietary	—	$9.00
DeepSeek R1 Distill Llama 70BOSS DeepSeek · Open Source	—	$0.50
DeepSeek R1 Distill Qwen 32BOSS DeepSeek · Open Source	—	$0.30
DeepSeek VL2OSS DeepSeek · Open Source · via Replicate	—	$2.80
DeepSeek VL2 SmallOSS DeepSeek · Open Source · via Replicate	—	$1.70
DeepSeek VL2 TinyOSS DeepSeek · Open Source · via Replicate	—	$0.90
DeepSeek-R1OSS DeepSeek · Open Source	—	$2.74
DeepSeek-R1-0528OSS DeepSeek · Open Source	—	$2.74
DeepSeek-V2.5OSS DeepSeek · Open Source	—	$0.42
DeepSeek-V3OSS DeepSeek · Open Source	—	$1.37
DeepSeek-V3 0324OSS DeepSeek · Open Source	—	$1.42
DeepSeek-V3.1OSS DeepSeek · Open Source	—	$1.27
DeepSeek-V3.2OSS DeepSeek · Open Source · via OpenRouter	—	$0.57
DeepSeek-V3.2 (Non-thinking)OSS DeepSeek · Open Source	—	$0.70
DeepSeek-V3.2-ExpOSS DeepSeek · Open Source	—	$0.68
DeepSeek-V4-Flash-0423OSS DeepSeek · Open Source	—	$0.30
DeepSeek-V4-Flash-0731OSS DeepSeek · Open Source	—	$1.76
DeepSeek-V4-Flash-MaxOSS DeepSeek · Open Source	—	$0.42
DeepSeek-V4-Flash-Vision-Exp DeepSeek · Proprietary	—	$0.88
DeepSeek-V4-Pro-0813OSS DeepSeek · Open Source	—	$5.28
DeepSeek-V4-Pro-MaxOSS DeepSeek · Open Source	—	$5.22

Showing 1–50 of 345 models

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The index

All Large Language Models

345 models across 36 providers. Search or jump to a lab — every model page stays linked here.

Cursor

2 models

Composer 2 Composer 2 Fast

xAI

17 models

Grok 4.6 Grok 4.5 Grok 4.3 Grok-4.1 Grok-4.1 Fast Non-Reasoning Grok-4.1 Fast Reasoning Grok-4.1 Thinking Grok 4 Fast Grok Code Fast 1 Grok-4 Fast Non-Reasoning Grok-4 Fast Reasoning Grok-4 Grok-3 Grok-3 Mini Grok-2 Grok-1.5V Grok-1.5

MiniMax

7 models

MiniMax M3 MiniMax M2.7 MiniMax M2.5 MiniMax M2.1 MiniMax M2 MiniMax M1 40K MiniMax M1 80K

Qwen

55 models

Qwen3.8 Flash Qwen3.8-Flash-Next Qwen3.8-27B Qwen3.8-2.4T-A95B Qwen3.8 Max Qwen3.7 Flash Qwen3.7-Plus Qwen3.7 Max Qwen3.6-27B Qwen3.6-35B-A3B Qwen3.6 Plus Qwen3.5-0.8B Qwen3.5-2B Qwen3.5-4B Qwen3.5-9B Qwen3.5-122B-A10B Qwen3.5-27B Qwen3.5-35B-A3B Qwen3.5-397B-A17B Qwen3 Max Qwen3 VL 235B A22B Instruct Qwen3 VL 235B A22B Thinking Qwen3 VL 30B A3B Instruct Qwen3 VL 30B A3B Thinking Qwen3 VL 32B Instruct Qwen3 VL 32B Thinking Qwen3 VL 4B Instruct Qwen3 VL 4B Thinking Qwen3 VL 8B Instruct Qwen3 VL 8B Thinking Qwen3-Next-80B-A3B-Instruct Qwen3-Next-80B-A3B-Thinking Qwen3-235B-A22B-Thinking-2507 Qwen3-235B-A22B-Instruct-2507 Qwen3 235B A22B Qwen3 30B A3B Qwen3 32B Qwen2.5-Omni-7B QwQ-32B Qwen2.5 VL 32B Instruct Qwen3-Coder 480B A35B Instruct Qwen2.5 VL 72B Instruct Qwen2.5 VL 7B Instruct Qwen3-Coder QvQ-72B-Preview QwQ-32B-Preview Qwen2.5 14B Instruct Qwen2.5 32B Instruct Qwen2.5 72B Instruct Qwen2.5 7B Instruct Qwen2.5-Coder 32B Instruct Qwen2.5-Coder 7B Instruct Qwen2-VL-72B-Instruct Qwen2 72B Instruct Qwen2 7B Instruct

AI21 Labs

2 models

Jamba 1.5 Large Jamba 1.5 Mini

Amazon

7 models

Nova 2 Lite Nova 2 Omni Nova 2 Pro Nova 2 Sonic Nova Lite Nova Micro Nova Pro

Baidu

2 models

ERNIE 5.0 ERNIE 4.5

ByteDance

4 models

Seed 2.1 Pro Seed 2.1 Turbo Seed 2.0 Lite Seed 2.0 Pro

Cohere

4 models

North Micro Vision Instruct North Mini Code 1.0 Command A+Command R+

IBM

2 models

IBM Granite 4.0 Tiny Preview Granite 3.3 8B Instruct

Inception

1 models

Mercury 2

inclusionAI

1 models

Ling-3.0-flash

LG AI Research

1 models

K-EXAONE-236B-A23B

Liquid AI

2 models

LFM2.5-VL-3B LFM2.5-2.6B

Meituan

4 models

LongCat-Flash-Lite LongCat-Flash-Thinking-2601 LongCat-Flash-Thinking LongCat-Flash-Chat

Microsoft

9 models

MAI-Code-1.1-Flash MAI-Code-1-Flash MAI-Thinking-1 Phi 4 Mini Phi-4-multimodal-instruct Phi 4 Phi-3.5-mini-instruct Phi-3.5-MoE-instruct Phi-3.5-vision-instruct

Moonshot AI

11 models

Kimi K3 Kimi K2.7 Code Kimi K2.7 Code HighSpeed Kimi K2.6 Kimi K2.5 Kimi K2 0905 Kimi K2-Instruct-0905 Kimi K2-Thinking-0905 Kimi K2 Base Kimi K2 Instruct Kimi-k1.5

Nous Research

1 models

Hermes 3 70B

NVIDIA

9 models

Nemotron 3.5 Lightning (30B A3B)Nemotron 3 Ultra (550B A55B)Nemotron 3 Super (120B A12B)Nemotron 3 Nano (30B A3B)Nemotron Nano 9B v2 Llama 3.1 Nemotron Ultra 253B v1 Llama 3.1 Nemotron Nano 8B V1 Llama-3.3 Nemotron Super 49B v1 Llama 3.1 Nemotron 70B Instruct

OpenBMB

1 models

MiniCPM-SALA

Poolside

2 models

Laguna S 2.1 Laguna XS 2.1

Sakana AI

1 models

Sakana Namazu

Sarvam AI

2 models

Sarvam-105B Sarvam-30B

StepFun

2 models

Step-3.5-Flash Step3-VL-10B

Tencent

1 models

Hy3

Thinking Machines

1 models

Inkling-Small

Unisound

1 models

Upstage

1 models

Solar Pro 4

Xiaomi

5 models

MiMo-V2.5-Pro MiMo-V2.5 MiMo-V2-Omni MiMo-V2-Pro MiMo-V2-Flash

Which model leads Mega Xcopa right now?

As of August 31, 2026, Phi-3.5-MoE-instruct by Microsoft is #1 for Mega Xcopa at 76.6%. Ranked by the Mega Xcopa score This board also tracks Mega Xcopa. Next on the same board: Phi-3.5-mini-instruct. This mega xcopa leaderboard ranks models by Mega Xcopa. 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)

Top 2 for mega xcopa. Ranked by the Mega Xcopa score Input and output are dollars per million tokens.
Rank	Model	Mega Xcopa	Input /M	Output /M
1	Phi-3.5-MoE-instruct	76.6%	$0.07	$0.14
2	Phi-3.5-mini-instruct	63.1%	$0.10	$0.10

Related LLM leaderboards

LLM Leaderboard Coding Math Agentic Reasoning Writing Science Finance Long Context Vision Open Source

Individual benchmark pages

Rank one eval at a time. All LLM benchmarks.

HLE SWE Bench Humanity's Last Exam (No Tools)Humanity's Last Exam (With Tools)Terminal-Bench 2.0 Terminal-Bench Terminal-Bench 2.1 Terminal-Bench 2 Terminal-Bench 3.0 ARC-AGI-1 Verified

Mega Xcopa FAQ

Who ranks #1 on the Mega Xcopa leaderboard?

As of August 31, 2026, Phi-3.5-MoE-instruct by Microsoft ranks #1 on Mega Xcopa at 76.6%. API pricing is $0.07/M input and $0.14/M output.

What are the top models on Mega Xcopa?

The current Mega Xcopa ranking as of August 31, 2026 is 1. Phi-3.5-MoE-instruct at 76.6%; 2. Phi-3.5-mini-instruct at 63.1%.

Which mega xcopa model is the cheapest?

Phi-3.5-mini-instruct is the cheapest scored model on this mega xcopa leaderboard at $0.10/M input and $0.10/M output ($0.20 blended). Phi-3.5-MoE-instruct still leads Mega Xcopa at 76.6%.

Should I always pick the #1 Mega Xcopa model?

Not automatically. Phi-3.5-MoE-instruct leads Mega Xcopa, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh Mega Xcopa against input/output price, context window, and related evals.

How often is the Mega Xcopa leaderboard updated?

Scores and API prices on this page are refreshed from published evals and provider rates. The snapshot is labeled August 31, 2026. Treat it as a current index, not a one-off blog post.

What is Mega Xcopa?

Mega Xcopa is a public LLM eval (the Mega Xcopa score). This page ranks models that have published a score, next to live API prices.

Where is the Mega Xcopa leaderboard?

This page is the Mega Xcopa leaderboard. Models are sorted by Mega Xcopa, 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 Mega Xcopa ranking different from the official board?

Official eval pages own the methodology. This page keeps the published Mega Xcopa score next to live API $/M so you can pick a production SKU, not only a trophy number.

You found the model. Now ship the product.

All Large Language Models

OpenAI

Anthropic

Google

Cursor

xAI

DeepSeek

MiniMax

Qwen

AI21 Labs

Amazon

Baidu

ByteDance

Cohere

IBM

Inception

inclusionAI

LG AI Research

Liquid AI

Meituan

Meta

Microsoft

Mistral

Moonshot AI

Nous Research

NVIDIA

OpenBMB

Poolside

Sakana AI

Sarvam AI

StepFun

Tencent

Thinking Machines

Unisound

Upstage

Xiaomi

Z AI

Which model leads Mega Xcopa right now?

Related LLM leaderboards

Individual benchmark pages

Mega Xcopa FAQ

Who ranks #1 on the Mega Xcopa leaderboard?

What are the top models on Mega Xcopa?

Which mega xcopa model is the cheapest?

Should I always pick the #1 Mega Xcopa model?

How often is the Mega Xcopa leaderboard updated?

What is Mega Xcopa?

Where is the Mega Xcopa leaderboard?

How is this Mega Xcopa ranking different from the official board?