whatmodel.sh / Falcon-H1R 7B

Falcon-H1R 7B

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Falcon-H1R 7B is an open-weights language model from TII, released January 2026. Its published size is 7.59B parameters and a 262k-token context window. Licence: falcon-llm.

60.0±1.1#195 of 719 LLMsfrom 12 benchmark results across 1 source

$ how it compares

The LLMs ranked either side of Falcon-H1R 7B, out of 828 with a score, then more from TII.

#modelscorewhereRAMreleased
231Qwen3 30B-A3B Instruct 2507 Alibaba60±1api $0.15/M +local~20GB2025-07
232Qwen3-VL 32B Instruct Alibaba60±1api $0.28/M +local~22GB2025-10
233Falcon-H1R 7B TII60±1local~6GB2026-01
234Gemini 2.0 Flash (001) Google60±1comparison only2025-02
235ERNIE 4.5 300B-A47B Baidu60±1local~97GB2025-06
more from TII
332Falcon-H1 34B Instruct TII54±3local~23GB2025-05
494Falcon-H1 7B Instruct TII46±3local~6GB2025-05
551Falcon3 7B Instruct TII44±3local~5.9GB2024-11

see all LLMs · find the ones that fit your machine

$ what it's good at

agent tasks▁▁▃▆█▆▅▅▅▄▃▁ #186 of 300 * · 20% of its score · 2 tests

Beats o1 (2024-12-17), o3-mini, DeepSeek R1 0528 here, though they rank higher overall. Trails SmolLM3 3B, Jamba 1.5 Mini, Mellum2 12B-A2.5B Instruct here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
τ²-bench Telecom lab25.4% ✎▁·▅█▆▅▂▃▃▂▃▁ beats 15/89very hard · avg 12%▇▇▇▇ 10%sharp · at its level · small run
Terminal-Bench Hard lab4.9% ✎▂▅▆▃▂▆▂▂█▅▅▂ beats 8/27very hard · avg 1.4%▇▇▇▇ 10%sharp · too hard for it
coding▁▁▁▃▆██▇▆▄▃▁ #204 of 458 * · 9.0% of its score · 2 tests

Beats Qwen3.5 4B, Qwen3-VL 32B Instruct here, though they rank higher overall. Trails QwQ-32B-Preview, Ministral 3 3B Reasoning 2512, DeepSeek-Coder-V2 Instruct (0724) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LiveCodeBench v6 (window unspecified) lab68.6% ✎█·▄·▄····▄·▄ beats 4/5medium · avg 42%▇▇▇ 7.1%at its level
SciCode main problems lab3.9% ✎▄··▄····█▄·▄ beats 1/5very hard · avg 3.8%▇ 1.9%too hard for it
math▁▂▃▅▆▅▄█▄▁▁▁ #124 of 398 · 39% of its score · 4 tests

Beats Claude Sonnet 4.6, MiniMax-M3, MiMo-V2.5 (310B-A15B) here, though they rank higher overall. Trails Olmo 3.1 32B Think, Granite 4.2 8B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
HMMT 2025 (edition unspecified) lab64.9% ✎▄··▄▄·▄····█ beats 5/5hard · avg 29%▇▇▇▇▇ 13%sharp · at its level
AIME 2024 lab88.1% ✎█▄···█·····▄ beats 5/5medium · avg 62%▇▇▇▇▇ 11%sharp
AIME 2025 lab83.1% ✎▄·█··▄····▄▄ beats 4/5medium · avg 53%▇▇▇▇ 10%sharp
MATH-500 lab97.4% ✎▄·▄·····█··█ beats 5/5very easy · avg 92%▇▇ 4.9%maxed out
other tests4 not in a task · 31% of its score
testresultvs the others in its rundifficultycountswhy
GPQA Diamond lab61.3% ✎█·········▂▂ beats 2/5hard · avg 45%▇▇▇▇▇▇ 15%sharp · at its level
Humanity's Last Exam lab11.1% ✎█··██···█·██ beats 5/5very hard · avg 3.8%▇▇▇ 7.7%typical
MMLU-Pro lab72.1% ✎█··█··███··█ beats 2/5medium · avg 57%▇▇▇ 6.6%at its level
IFBench (aggregation unspecified) lab53.4% ✎███···██···█ beats 4/5hard · avg 35%▇ 2.0%at its level

$ where to run it

llama.cpp · recommended

version

  1. 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 | sh
    Windows
    irm https://llama.app/install.ps1 | iex

    other ways to install ↗

  2. Run Falcon-H1R 7B · needs ~5.05 GB · from huggingface.co/tiiuae (official)
    chat in the terminal
    llama cli -hf tiiuae/Falcon-H1R-7B-GGUF:Q4_K_M
  3. Or start a local server and open the address it prints (http://localhost:9931)
    llama serve -hf tiiuae/Falcon-H1R-7B-GGUF:Q4_K_M

LM Studio

version

  1. Install LM Studio · Open the app once before using the lms command.

    download it (macOS / Windows / Linux) ↗

  2. Run Falcon-H1R 7B · needs ~5.05 GB · from huggingface.co/tiiuae (official)

    open in LM Studio ↗

  3. Or download it in the terminal
    lms get https://huggingface.co/tiiuae/Falcon-H1R-7B-GGUF@Q4_K_M -y
  4. Then run lms ls to see its name, and lms chat followed by that name

Ollama

version

  1. Install Ollama

    download it (macOS / Windows) ↗

    Linux
    curl -fsSL https://ollama.com/install.sh | sh
  2. Run Falcon-H1R 7B · needs ~5.05 GB · from huggingface.co/tiiuae (official)
    chat in the terminal
    ollama run hf.co/tiiuae/Falcon-H1R-7B-GGUF:Q4_K_M

MLX (Mac)

version

  1. Install MLX (Mac) · Apple silicon Macs only, text only.
    with uv
    uv tool install mlx-lm
    or
    pip install mlx-lm
  2. Run Falcon-H1R 7B · needs ~4.3 GB, Mac only · from huggingface.co/mlx-community
    chat in the terminal
    mlx_lm.chat --model mlx-community/Falcon-H1R-7B-4bit
  3. Or start an OpenAI-compatible server at http://localhost:8080/v1
    mlx_lm.server --model mlx-community/Falcon-H1R-7B-4bit

Official weights and documentation: huggingface.co/tiiuae ↗

$ how the score was worked out · Falcon-H1R: Pushing the Reaso… 99%

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

sourceresultsshare of the scorelicence
Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling · lab-reported12▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%CC BY 4.0
prior · pull toward the middle▇ 1%
weighted average= 60.0

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

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