Who ranks #1 on the MATH 500 leaderboard?
As of August 20, 2026, LongCat-Flash-Thinking by Meituan ranks #1 on MATH 500 at 99.2%. API pricing is $0.30/M input and $1.20/M output.
As of August 20, 2026, LongCat-Flash-Thinking is #1 for MATH 500 at 99.2%. Ranked by MATH-500: textbook and contest math problems. 42 models in this index have a published MATH 500 score. MATH 500 leaderboard with live API prices. MATH-500 — a 500-problem subset of MATH covering competition-level mathematical reasoning.
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As of August 20, 2026, LongCat-Flash-Thinking by Meituan is #1 for MATH 500 at 99.2%. Ranked by MATH-500: textbook and contest math problems. This board also tracks MATH 500. Next on the same board: GLM-4.5 and GLM-4.5-Air. This math 500 leaderboard ranks models by MATH 500. 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 | MATH 500 | Input /M | Output /M |
|---|---|---|---|---|
| 1 | LongCat-Flash-Thinking | 99.2% | $0.30 | $1.20 |
| 2 | GLM-4.5 | 98.2% | $0.60 | $2.20 |
| 3 | GLM-4.5-Air | 98.1% | $0.20 | $1.10 |
| 4 | o3-mini | 97.9% | $1.10 | $4.40 |
| 5 | Nemotron Nano 9B v2 | 97.8% | — | — |
| 6 | Kimi K2-Instruct-0905 | 97.4% | $0.60 | $2.50 |
| 7 | Kimi K2 Instruct | 97.4% | $0.50 | $0.50 |
| 8 | DeepSeek-R1 | 97.3% | $0.55 | $2.19 |
Rank one eval at a time. All LLM benchmarks.
As of August 20, 2026, LongCat-Flash-Thinking by Meituan ranks #1 on MATH 500 at 99.2%. API pricing is $0.30/M input and $1.20/M output.
The current MATH 500 ranking as of August 20, 2026 is 1. LongCat-Flash-Thinking at 99.2%; 2. GLM-4.5 at 98.2%; 3. GLM-4.5-Air at 98.1%.
Qwen3 235B A22B is the cheapest scored model on this math 500 leaderboard at $0.10/M input and $0.10/M output ($0.20 blended). LongCat-Flash-Thinking still leads MATH 500 at 99.2%.
Not automatically. LongCat-Flash-Thinking leads MATH 500, but a cheaper scored model can be the better production choice if the quality gap is small. Use the table to weigh MATH 500 against input/output price, context window, and related evals.
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.
MATH-500 — a 500-problem subset of MATH covering competition-level mathematical reasoning. This page ranks models that have published a MATH 500 score, with live API token prices on the same row.
This page is the MATH 500 leaderboard. Models are sorted by MATH 500, 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.
Official eval pages own the methodology. This page keeps the published MATH 500 score next to live API $/M so you can pick a production SKU, not only a trophy number.