whatmodel.sh / Krutrim-2 Instruct
Krutrim-2 Instruct
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Krutrim-2 Instruct is an open-weights language model from Krutrim (Ola), released February 2025. Licence: other (krutrim-community-license-agreement-version-1.0).
Catalogue identity notes
Maker repo krutrim-ai-labs/Krutrim-2-instruct @b2f4411: licence tag other (krutrim-community-license-agreement-version-1.0). Released 2025-02: month the maker's Hugging Face repo was created (createdAt 2025-02-02).
$ how it compares
The LLMs ranked either side of Krutrim-2 Instruct, out of 1132 with a score.
| # | model | score | where |
|---|---|---|---|
| 415 |  Qwen2.5 Coder 14B Instruct | 55±1 | local |
| 416 | Qwen3-VL 8B Instruct | 55±1 | api $0.31/M +local |
| 417 | Krutrim-2 Instruct | 55±5 | local |
| 418 |  Spark-X2.5 1.7B | 55±1 | local |
| 419 |  Dracarys2-72B-Instruct | 55±3 | local |
$ what it's good at
other tests1 not in a task · 91% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| HindiGen-v1 3C3H score (Inception, Claude 3.5 Sonnet judge) | 59.6% ✎ | ▁▁▁▁·▂·█▆█▇▁ beats 13/31 | 91% |
$ where to run it
llama.cpp · recommended
version
- Install llama.cpp · Homebrew and winget installs name the commands llama-cli and llama-server instead.macOS / Linux
curl -LsSf https://llama.app/install.sh | shWindowsirm https://llama.app/install.ps1 | iex - Run Krutrim-2 Instruct · needs ~7.5 GB · from huggingface.co/bartowskichat in the terminal
llama cli -hf bartowski/krutrim-ai-labs_Krutrim-2-instruct-GGUF:Q4_K_M - Or start a local server and open the address it prints (http://localhost:9931)
llama serve -hf bartowski/krutrim-ai-labs_Krutrim-2-instruct-GGUF:Q4_K_M
LM Studio
version
- Install LM Studio · Open the app once before using the lms command.
- Run Krutrim-2 Instruct · needs ~7.5 GB · from huggingface.co/bartowski
- Or download it in the terminal
lms get https://huggingface.co/bartowski/krutrim-ai-labs_Krutrim-2-instruct-GGUF@Q4_K_M -y - Then run lms ls to see its name, and lms chat followed by that name
Ollama
version
- Install Ollama
download it (macOS / Windows) ↗
Linuxcurl -fsSL https://ollama.com/install.sh | sh - Run Krutrim-2 Instruct · needs ~7.5 GB · from huggingface.co/bartowskichat in the terminal
ollama run hf.co/bartowski/krutrim-ai-labs_Krutrim-2-instruct-GGUF:Q4_K_M
Other ways to run it
- Run it as published · needs ~48.99 GB · from huggingface.co/krutrim-ai-labs (official)
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='krutrim-ai-labs/Krutrim-2-instruct', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
Official weights and documentation: huggingface.co/krutrim-ai-labs ↗
$ how the score was worked out · Inception Arabic/Hindi leader… 91%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 Inception Arabic/Hindi leaderboards (AraGen-v3, HindiGen-v1, Arabic IFEval) | 1 | 91% |
| prior · pull toward the middle | 9% | |
| weighted average | = 55.1 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json