Tenstorrent
Open RISC-V AI hardware
- Version
- Blackhole
- Cost
- from $999/unit
- Model
- Tensix cores
AWS · #5 most active of 18 in Chips & Compute
Trn2 UltraServers and Project Rainier capacity, programmed through the Neuron SDK.
Trust score · Mostly verified
2 data points checked · 2026-09-11
Current version
Trainium2
Entry cost
Pricing not published; available via AWS EC2 instance pricing.
Changes / 30d
5
The short answers · verified September 15, 2026
Source: AWS — aws.amazon.com · Reusable under CC BY 4.0 — cite Tomorrow
Pricing not published; available via AWS EC2 instance pricing.
Entry price over time
Not enough pricing history yet — we start charting from the second observation.
Neuron compiler
AWS
Trainium2
AWS
Context window
—
Public API
yes
Multi-model routing
no
Other tracked products running on the same foundation models — a quick read on how much of the catalog moves when one of these models changes.
green disclosed · amber inferred · grey unattributed. Aliases are folded into one model; provider concentration counts only models with an established vendor.
Reference data. Each figure is whatever the source actually said — weekly users, downloads, revenue run-rate — with its own definition and date. These are not comparable between tools and are never used to rank anything.
No public usage figure on record for this product.
Tenstorrent
Open RISC-V AI hardware
Inference-first TPU pods
Cerebras
Wafer-scale inference and training
NVIDIA
GB200/B200 rack-scale AI systems
Intel
Cost-focused training and inference accelerator.
SambaNova
Dataflow chips for model serving
New capabilities: Gen AI training, Gen AI inference, 3.2 Tbps EFAv3
70 tracked74 tracked · +Gen AI training, Gen AI inference, 3.2 Tbps EFAv3, 1.5 TB HBM3
sourceNew capabilities: Up to 20.8 FP8 Petaflops (Trn2), Up to 83.2 FP8 Petaflops (UltraServer), Up to 6 TB HBM (UltraServer)
67 tracked70 tracked · +Up to 20.8 FP8 Petaflops (Trn2), Up to 83.2 FP8 Petaflops (UltraServer), Up to 6 TB HBM (UltraServer)
sourceNew capabilities: Elastic Fabric Adapter (EFAv3), FP8 compute support
65 tracked67 tracked · +Elastic Fabric Adapter (EFAv3), FP8 compute support
sourceNew capabilities: Gen AI Training, AWS Nitro System
63 tracked65 tracked · +Gen AI Training, AWS Nitro System
sourceNew capabilities: ML Training, ML Inference, High Bandwidth Memory
57 tracked60 tracked · +ML Training, ML Inference, High Bandwidth Memory
sourceNew capabilities: AWS Nitro System encryption
54 tracked55 tracked · +AWS Nitro System encryption
sourceNew capabilities: generative AI training, generative AI inference
52 tracked54 tracked · +generative AI training, generative AI inference
sourceNew capabilities: PyTorch integration, JAX integration
50 tracked52 tracked · +PyTorch integration, JAX integration
sourceNew capabilities: Generative AI Inference, AWS Neuron SDK
48 tracked50 tracked · +Generative AI Inference, AWS Neuron SDK
sourceNew capabilities: NeuronLink, EC2 UltraClusters
46 tracked48 tracked · +NeuronLink, EC2 UltraClusters
sourceNew capabilities: Elastic Fabric Adapter (EFAv3) networking
45 tracked46 tracked · +Elastic Fabric Adapter (EFAv3) networking
sourceNew capabilities: Generative AI Training, Inference, NeuronLink Interconnect
38 tracked45 tracked · +Generative AI Training, Inference, NeuronLink Interconnect, EFAv3 Networking, PyTorch Support, JAX Support, vLLM Support
sourceNew capabilities: Configurable FP8 (cFP8) support, Stochastic rounding & 4x sparsity (16:4), Local NVMe storage up to 8 TB
2910
sourceNew capabilities: 16 AWS Trainium2 chips, Up to 20.8 FP8 PFLOPS compute, 46 TBps memory bandwidth
2210
sourceNew capabilities: NeuronLink interconnect, 1.5 TB HBM3 accelerator memory, Up to 20.8 FP8 Petaflops of compute
1410
sourceNew capabilities: Generative AI training, Generative AI inference, Up to 20.8 FP8 petaflops
410
sourceNew capabilities: Gen AI Compute, Trainium2 chips, 20.8 FP8 Petaflops
10 tracked17 tracked · +Gen AI Compute, Trainium2 chips, 20.8 FP8 Petaflops, 1.5 TB HBM3 memory, EFAv3 networking, Neuron SDK support, PyTorch & JAX support
sourceNew capabilities: Trn2 instances, Trn2 UltraServers, 16 Trainium2 chips
10 tracked20 tracked · +Trn2 instances, Trn2 UltraServers, 16 Trainium2 chips, 64 Trainium2 chips, 20.8 FP8 petaflops, 83.2 FP8 petaflops, 1.5 TB HBM3, 6 TB HBM3, 3.2 Tbps EFAv3, 12.8 Tbps EFAv3
sourceNew capabilities: 1.5 TB HBM3 memory, 3.2 Tbps EFAv3 networking, NeuronLink interconnect
10 tracked19 tracked · +1.5 TB HBM3 memory, 3.2 Tbps EFAv3 networking, NeuronLink interconnect, AWS Nitro System encryption, EC2 UltraClusters scaling, FP32/TF32/BF16/FP16/cFP8 support, Stochastic rounding, 4x sparsity (16:4), Neuron Kernel Interface (NKI)
sourceNew capabilities: 20.8 FP8 Petaflops, 1.5 TB HBM3, 3.2 Tbps EFAv3
9 tracked18 tracked · +20.8 FP8 Petaflops, 1.5 TB HBM3, 3.2 Tbps EFAv3, 8 TB local NVMe, FP32 support, TF32 support, BF16 support, FP16 support, cFP8 support
sourceNew capabilities: Trainium2, NeuronLink, Up to 20.8 FP8 Petaflops
10 tracked18 tracked · +Trainium2, NeuronLink, Up to 20.8 FP8 Petaflops, 1.5 TB HBM3 memory, 46 TBps memory bandwidth, 3.2 Tbps EFAv3 networking, FP8 cFP8 support, Neuron SDK
sourceNew capabilities: Generative AI training, Generative AI inference, NeuronLink chip interconnect
8 tracked18 tracked · +Generative AI training, Generative AI inference, NeuronLink chip interconnect, EFAv3 networking, AWS Nitro System encryption, FP8 FP16 FP32 TF32 BF16 support, Up to 83.2 FP8 petaflops, Up to 6 TB HBM3 memory, Local NVMe storage, PyTorch and JAX support
sourceStraight head-to-head pages against the busiest products in Chips & Compute.
Free to cite and reuse under CC BY 4.0. Permalink: https://tomorrow.aliensquad.ai/tools/aws-trainium
Tomorrow. (2026). AWS Trainium2 — version, pricing and model stack [Data set entry]. AlienSquad. Retrieved 2026-09-17, from https://tomorrow.aliensquad.ai/tools/aws-trainium
@misc{tomorrow-tools-aws-trainium,
author = {{Tomorrow}},
title = {AWS Trainium2 — version, pricing and model stack},
year = {2026},
publisher = {AlienSquad},
howpublished = {\url{https://tomorrow.aliensquad.ai/tools/aws-trainium}},
note = {Accessed: 2026-09-17}
}