Reka Flash offers a cost-effective, high-context window solution for multimodal tasks, excelling in speed for its price point, though it sits at the lower end of intelligence benchmarks.
Reka Flash (Sep '24) emerges as a compelling option for developers seeking a balance between performance and cost, particularly for applications that benefit from multimodal input and a substantial context window. Positioned as a non-reasoning model, it is engineered for efficiency in tasks where complex logical inference is not the primary requirement, such as content generation, summarization, or data extraction from diverse inputs.
Despite its classification among the least intelligent models on the Artificial Analysis Intelligence Index, scoring 19 against an average of 28 for comparable models, Reka Flash distinguishes itself through its robust technical specifications. It boasts an impressive 128k token context window, enabling it to process extensive amounts of information in a single query. Furthermore, its multimodal capabilities, including support for image input, open up a wide array of use cases that leverage visual data alongside text.
From a performance perspective, Reka Flash delivers a median output speed of 71 tokens per second. While this is slower than the overall market average of 94 tokens per second, it represents a competitive offering within its price segment, especially for a model with its context handling and multimodal features. The latency, or time to first token (TTFT), stands at 1.31 seconds, indicating a moderate response time suitable for many interactive applications.
Pricing for Reka Flash is structured to be generally accessible, with input tokens at $0.20 per 1M and output tokens at $0.80 per 1M. This input pricing is moderately competitive, aligning closely with the market average. However, the output token price is somewhat higher than average, suggesting that applications requiring very verbose outputs might incur higher costs. The blended price, calculated at a 3:1 input-to-output token ratio, is $0.35 per 1M tokens, highlighting its cost-effectiveness for scenarios with more input than output.
In summary, Reka Flash is a strategic choice for developers prioritizing high-volume, multimodal content processing and generation where the core task does not demand advanced reasoning. Its large context window and competitive speed, coupled with a reasonable overall cost structure, make it a strong contender for specific, well-defined applications.
19 (#58 / 77 / 1 out of 4 units)
71 tokens/s
$0.20 /1M tokens
$0.80 /1M tokens
N/A Unknown
1.31 seconds
| Spec | Details |
|---|---|
| Owner | Reka AI |
| License | Proprietary |
| Context Window | 128k tokens |
| Modality | Multimodal (Text, Image) |
| Intelligence Index | 19 (1/4 units) |
| Output Speed | 71 tokens/s |
| Latency (TTFT) | 1.31 seconds |
| Input Token Price | $0.20 / 1M tokens |
| Output Token Price | $0.80 / 1M tokens |
| Blended Price (3:1 Input:Output) | $0.35 / 1M tokens |
| Model Type | Non-reasoning |
| Release Date | September 2024 |
Reka Flash is exclusively offered by Reka AI, ensuring a direct and integrated experience with the model's developers. This singular provider model simplifies choice but emphasizes the importance of understanding Reka AI's service level agreements and support.
| Priority | Pick | Why | Tradeoff to accept |
|---|---|---|---|
| Balanced Performance | Reka AI | As the sole provider, Reka AI offers direct access to Reka Flash, ensuring optimal integration and performance as intended by the model's creators. | No alternative providers for comparison or redundancy. |
Note: Provider performance and pricing are subject to change. Always verify current offerings directly with the provider.
Understanding the real-world cost implications of Reka Flash involves analyzing common use cases and estimating token consumption. The following scenarios illustrate potential costs based on Reka AI's pricing structure ($0.20/1M input, $0.80/1M output).
| Scenario | Input | Output | What it represents | Estimated cost |
|---|---|---|---|---|
| Image Captioning & Description | 1 image + 50 tokens text prompt | 150 tokens detailed description | Generating descriptive text for visual content, e.g., e-commerce product descriptions or accessibility alt-text. | $0.000130 |
| Long Document Summarization | 10,000 tokens document | 500 tokens summary | Condensing extensive reports or articles into concise summaries for quick review. | $0.002400 |
| Multimodal Data Extraction | 1 image + 2,000 tokens invoice text | 200 tokens structured data (JSON) | Extracting key information from scanned documents or images combined with text. | $0.000560 |
| Creative Content Generation | 500 tokens creative brief | 2,000 tokens blog post draft | Drafting marketing copy, blog posts, or creative narratives based on specific prompts. | $0.001700 |
| Customer Support Response Generation | 1,500 tokens customer query & history | 300 tokens personalized response | Automating initial responses or drafting suggestions for customer service agents. | $0.000660 |
| Code Snippet Generation | 200 tokens problem description | 800 tokens code snippet + explanation | Assisting developers by generating boilerplate code or function implementations. | $0.000680 |
Reka Flash demonstrates cost-effectiveness for tasks with a higher input-to-output token ratio, especially when leveraging its multimodal capabilities. However, scenarios demanding very verbose outputs will see costs rise due to the higher output token price. Strategic prompt engineering to control output length is key to optimizing expenses.
Optimizing costs with Reka Flash involves a multi-faceted approach, balancing its strengths with its pricing structure. Here are key strategies to maximize efficiency and minimize expenditure.
Given Reka Flash's higher output token price, crafting prompts that encourage concise yet comprehensive responses is paramount. Avoid open-ended prompts that might lead to excessive verbosity.
The 128k context window is a significant asset, but using it indiscriminately can lead to higher input costs. Be mindful of what information truly needs to be included in each prompt.
Reka Flash's image input capability is powerful. Ensure you're using it efficiently to avoid unnecessary processing or redundant information.
Regularly review your API usage logs and costs to identify patterns and areas for optimization. This data-driven approach is crucial for long-term cost management.
Reka Flash (Sep '24) is a multimodal, non-reasoning AI model developed by Reka AI. It is designed for efficient processing of text and image inputs, offering a large 128k token context window and competitive speed for its price point, making it suitable for a wide range of content generation and data extraction tasks.
Its primary strengths include its multimodal capabilities (image input), a very large 128k token context window, and its cost-effectiveness, particularly for input-heavy workflows. It also offers a respectable output speed for its class, making it a strong contender for high-volume, non-reasoning tasks.
Reka Flash is classified as a non-reasoning model and scores lower on intelligence benchmarks, meaning it may not be ideal for tasks requiring complex logical inference or deep understanding. Its output token price is also somewhat higher than average, and its overall speed is not as fast as the top-tier models.
Yes, Reka Flash is a multimodal model that fully supports image input, allowing users to incorporate visual data alongside text in their prompts for tasks like image captioning, visual question answering, and multimodal data extraction.
Reka Flash features an impressive 128k token context window, enabling it to process and understand very long documents, extensive chat histories, or large datasets within a single API call.
Reka Flash is priced at $0.20 per 1 million input tokens and $0.80 per 1 million output tokens. A blended price of $0.35 per 1 million tokens is also provided, calculated based on a 3:1 input-to-output token ratio.
Ideal use cases include large-scale document summarization, multimodal content generation (e.g., generating descriptions from images), data extraction from complex documents, automated customer support responses, and creative writing tasks where advanced reasoning is not the primary bottleneck.