MRMP Bench· a Persian benchmark for AI models
Which AI model is actually better?
Every model sits the same fixed Persian test: a 20-question report card and 8 interactive builds, from an arcade game and a santur to a Persian calendar and a 3D Azadi Tower. Code, a real browser and a jury from three companies give the score. Try every build yourself, right here.
13models published
20report-card questions · 40 points
8interactive builds · 60 points
3jurors from three companies
01Current champion
02Leaderboard
Each model’s score is the mean of its runs (a model with one run so far is “provisional”) · cost = what the model itself charged for the whole test, jury not included| # | Model | Tier | MRMP score | Report card | Showcase | Mohsen’s take | Cost of answers | Speed |
|---|---|---|---|---|---|---|---|---|
| 01 | Anthropic: Claude Opus 5.5 anthropic/claude-opus-5.5 | S | 98.59 between 97.17 and 100 | 39 / 40 | 59.59 / 60 | – | $5.12 | 137 tok/s |
| 02 | OpenAI: GPT-6.1 Sol openai/gpt-6.1-sol | S | 94.42 between 92.71 and 96.13 | 38 / 40 | 56.42 / 60 | – | $1.01 | 59 tok/s |
| 03 | SpaceXAI: Grok 4.7 x-ai/grok-4.7 | S | 94.13Provisional | 36 / 40 | 58.13 / 60 | – | $3.40 | 134 tok/s |
| 04 | Google: Gemini 3.8 Flash google/gemini-3.8-flash | S | 93.03 between 92.83 and 93.23 | 36 / 40 | 57.03 / 60 | – | 74.8¢ | 179 tok/s |
| 05 | Google: Gemini 4 Argon google/gemini-4-argon | S | 90.85 between 89.23 and 92.46 | 33 / 40 | 57.85 / 60 | – | $1.33 | 85 tok/s |
| 06 | OpenAI: GPT-6 Luna openai/gpt-6-luna | S | 90.15 between 89.61 and 90.69 | 35 / 40 | 55.15 / 60 | – | 5.6¢ | 155 tok/s |
| 07 | MoonshotAI: Kimi K3 moonshotai/kimi-k3 | A | 83.06Provisional | 36 / 40 | 47.06 / 60 | – | $3.37 | 122 tok/s |
| 08 | DeepSeek V4 Pro 0813 deepseek/deepseek-v4-pro-0813 | B | 79.87Provisional | 28 / 40 | 51.87 / 60 | – | 16.8¢ | 176 tok/s |
| 09 | Qwen3.8 Max (0902) qwen/qwen3.8-max-0902 | B | 77.75Provisional | 36 / 40 | 41.75 / 60 | – | $3.03 | 54 tok/s |
| 10 | DeepSeek V4 Flash 0423 deepseek/deepseek-v4-flash | B | 68.78 between 62.02 and 76.4 | 26 / 40 | 42.78 / 60 | – | 2.3¢ | 112 tok/s |
| 11 | Anthropic: Claude Sonnet 5.5 anthropic/claude-sonnet-5.5 | C | 63.55Provisional | 34 / 40 | 29.55 / 60 | – | $4.02 | 202 tok/s |
| 12 | Z.ai: GLM 5.3 FlashX z-ai/glm-5.3-flashx | C | 62.9Provisional | 34 / 40 | 28.9 / 60 | – | 68.9¢ | 258 tok/s |
| 13 | Qwen3.8 Flash qwen/qwen3.8-flash | C | 54.34 between 52.96 and 55.71 | 29 / 40 | 25.34 / 60 | – | 31.6¢ | 72 tok/s |
Costs are in US dollars.
03Best build per challenge
The best build of each showcase challenge. Open a card to see every model’s build for that challenge.Simorgh FlightS1
Anthropic: Claude Opus 5.5 · 7.5 of 7.5Ant ColonyS2
OpenAI: GPT-6.1 Sol · 7.5 of 7.53D Azadi TowerS3
Anthropic: Claude Opus 5.5 · 7.5 of 7.5Virtual SanturS4
Anthropic: Claude Opus 5.5 · 7.5 of 7.5Autumn Book CaféS5
Anthropic: Claude Opus 5.5 · 7.5 of 7.5Persian CalendarS6
Anthropic: Claude Opus 5.5 · 7.5 of 7.5Girih TilesS7
Anthropic: Claude Opus 5.5 · 7.5 of 7.5BazaarchehS8
Anthropic: Claude Opus 5.5 · 7.5 of 7.504Quality versus cost
Each dot is a model. Higher and further left (cheaper) is better value. Cost is what the model itself charged to answer the whole test, without the jury. The cost axis is logarithmic.
YouTube · @MrMpAI
Every new model, a new episode
I review each model’s results on camera on my YouTube channel: I run its builds, compare them with the champion and give my own verdict. The videos are in Persian.