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Overview

Reka AI is a multimodal AI company founded by former DeepMind, Meta, and Google Brain researchers. Their unique multimodal architecture handles text, code, images, video, and audio natively in a single model. As of 2026, lineup includes Reka Core (frontier-class), Reka Flash 3 (efficient mid-tier), Reka Edge, and Reka Spark.

Lineup

ModelParamsUse Case
Reka Core67BFrontier-class multimodal
Reka Flash 321BEfficient, general-purpose
Reka Edge7BEdge devices
Reka Spark2BUltra-lightweight

Reka Core (Frontier Class)

67B multimodal model handling text, images, video, and audio natively.

Benchmarks

  • Competitive with GPT-4V on image QA (MMMU, VQAv2)
  • Ranks 2nd in blind human evaluation of multimodal chat
  • Outperforms Claude 3 Opus in evaluations

Reka Flash 3 (2026 Latest)

21B general-purpose, instruction-tuned model.

MetricValue
Params21B
Context32K
OptimizationReinforcement learning
Quantization11GB at 4-bit
ReasoningExplicit thinking tags
  • Excels at chat, coding, instruction following, function calling
  • ELO score improved by 43 points (internal)
  • Overall quality: 66.1% → 72.2%

Key Features

1. Native Multimodal

Handles text, images, video, and audio in a unified model. Supports temporal video understanding and environmental sound recognition.

2. OCR & Document Understanding

Strong at documents, tables, charts, and diagrams.

3. Function Calling

Structured output for function calling.

4. Efficient Quantization

Flash 3 fits in 11GB at 4-bit — runs on standard GPUs.

5. Explicit Reasoning Tags

Flash 3 visualizes its thought process with explicit reasoning tags.

Strengths

  • Native multimodal (including video and audio)
  • Multiple sizes (67B/21B/7B/2B)
  • Reka Core ranks 2nd in multimodal chat
  • Function calling and structured output
  • Efficient quantization (11GB for Flash 3)
  • Native video/audio understanding

Weaknesses

  • Low brand awareness
  • Limited developer tools
  • Small ecosystem
  • Limited Japanese support
  • Flash 3 context is 32K (shorter than competitors)

Official Resources

公式サイト