Tweet: [https://x.com/RekaAILabs/status/1899481289495031825](https://x.com/RekaAILabs/status/1899481289495031825)
HuggingFace: [https://huggingface.co/RekaAI/reka-flash-3](https://huggingface.co/RekaAI/reka-flash-3)
Blog: [https://www.reka.ai/news/introducing-reka-flash](https://www.reka.ai/news/introducing-reka-flash)
Reka
Reka Flash Deprecated
Fast and capable 21B model outperforming larger models while delivering outsized value.
Unknown
N/A context
128,000 tokens output
Text
Model Overview
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Provider
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Reka
Input Context Window
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N/A
tokens
Maximum Output Tokens
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128,000 tokens
tokens
Open Source
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No
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Unknown
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Unknown
API Providers
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Reka
Modalities
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Text
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Input tokens
N/A
Per million tokens
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Per million tokens
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maxTemperature
1
maxResponseSize
128,000 tokens
API Access & Providers
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Reka
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Community discussion
What people think about Reka Flash Deprecated
Reka Flash Deprecated discussions are most active in r/LocalLLaMA, r/SillyTavernAI, r/24gb.
Top Reddit threads cluster around benchmark and model-comparison threads, safety and censorship questions, coding workflow discussions. The strongest match in this snapshot has 315 upvotes and 80 comments.
**From DavidAU;**
This model has been augmented, and uses the NEO Imatrix dataset. Testing has shown a decrease in reasoning tokens up to 50%.
This model is also uncensored. (YES! - from the "factory").
In "head to head" testing this model reasoning more smoothly, rarely gets "lost in the woods" and has stronger output.
And even the LOWEST quants it performs very strongly... with IQ2\_S being usable for reasoning.
Lastly: This model is reasoning/temp stable. Meaning you can crank the temp, and the reasoning is sound too.
7 Examples generation at repo, detailed instructions, additional system prompts to augment generation further and full quant repo here: [https://huggingface.co/DavidAU/Reka-Flash-3-21B-Reasoning-Uncensored-MAX-NEO-Imatrix-GGUF](https://huggingface.co/DavidAU/Reka-Flash-3-21B-Reasoning-Uncensored-MAX-NEO-Imatrix-GGUF)
**Tech NOTE:**
This was a test case to see what augment(s) used during quantization would improve a reasoning model along with a number of different Imatrix datasets and augment options.
I am still investigate/testing different options at this time to apply not only to this model, but other reasoning models too in terms of Imatrix dataset construction, content, and generation and augment options.
**For 37 more "reasoning/thinking models" go here: (all types,sizes, archs)**
[https://huggingface.co/collections/DavidAU/d-au-thinking-reasoning-models-reg-and-moes-67a41ec81d9df996fd1cdd60](https://huggingface.co/collections/DavidAU/d-au-thinking-reasoning-models-reg-and-moes-67a41ec81d9df996fd1cdd60)
**Service Note - Mistral Small 3.1 - 24B, "Creative" issues:**
For those that found/find the new Mistral model somewhat flat (creatively) I have posted a System prompt here:
[https://huggingface.co/DavidAU/Mistral-Small-3.1-24B-Instruct-2503-MAX-NEO-Imatrix-GGUF](https://huggingface.co/DavidAU/Mistral-Small-3.1-24B-Instruct-2503-MAX-NEO-Imatrix-GGUF)
(option #3) to improve it - it can be used with normal / augmented - it performs the same function.
I don't expect Ollama to have every finetuned models on their main library, and I understand that you can import gguf models from hugging face.
Still, it seems pretty odd that they're missing Reka Flash-3.2, SmolLM3, GLM-4. I believe other platforms like LMStudio, MLX, unsloth, etc have them.
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