Reka Core
Reka AI · dense · 70B parameters · 128,000 context
Parameters
70B
Context Window
125K tokens
Architecture
Dense
Best GPU
B100 SXM
Cheapest API
$15.00/M
Quality Score
76/100
Intelligence Brief
Reka Core is a 70B parameter DENSE model from Reka AI, featuring Grouped Query Attention (GQA) with 64 layers and 8,192 hidden dimensions. With a 128,000 token context window, it supports tools, vision, structured output, code, math, multilingual. On standardized benchmarks, it achieves MMLU 79, HumanEval 50, GSM8K 82. The most cost-effective API deployment is via reka at $15.00/M output tokens. For self-hosted inference, B100 SXM delivers optimal throughput at $4271/month.
Architecture Details
Memory Requirements
BF16 Weights
140.0 GB
FP8 Weights
70.0 GB
INT4 Weights
35.0 GB
GPU Compatibility Matrix
Reka Core is compatible with 38% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 1 GPU · tensorrt-llm
98/100
score
Throughput
492.8 tok/s
Latency (ITL)
2.0ms
Est. TTFT
0ms
Cost/Month
$4271
Cost/M Tokens
$3.30
BF16 · 1 GPU · tensorrt-llm
98/100
score
Throughput
492.8 tok/s
Latency (ITL)
2.0ms
Est. TTFT
0ms
Cost/Month
$6169
Cost/M Tokens
$4.76
BF16 · 2 GPUs · tensorrt-llm
95/100
score
Throughput
450.7 tok/s
Latency (ITL)
2.2ms
Est. TTFT
0ms
Cost/Month
$1879
Cost/M Tokens
$1.59
Deployment Options
API Deployment
reka
$15.00/M
output tokens
Single GPU
B100 SXM
$4271/mo
Min VRAM: 70 GB
Multi-GPU
H20 x2
450.7 tok/s
TP· $1879/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| reka | $3.00 | $15.00 | Cheapest |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| rekaBest Value | $3.00 | $15.00 | $90 |
Cost per 1,000 Requests
Short (500 tok)
$4.50
via reka
Medium (2K tok)
$18.00
via reka
Long (8K tok)
$54.00
via reka
Performance Estimates
Throughput by GPU
VRAM Breakdown (B100 SXM, BF16)
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Reka Core
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does Reka Core need for inference?
Reka Core requires approximately 140.0 GB of VRAM at BF16 precision, 70.0 GB at FP8, or 35.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (131072 bytes per token) and activations (~3.00 GB).
What is the best GPU for Reka Core?
The top recommended GPU for Reka Core is the B100 SXM using BF16 precision. It achieves approximately 492.8 tokens/sec at an estimated cost of $4271/month ($3.30/M tokens). Score: 98/100.
How much does Reka Core inference cost?
Reka Core API inference starts from $3.00/M input tokens and $15.00/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.