SWE-2 Flash Description
SWE-2 Flash is a high-speed AI software engineering model developed by Cognition for automated coding, development workflows, and technical problem-solving. The model is based on Inkling-Small from Thinking Machines and uses a mixture-of-experts architecture containing 276 billion total parameters and 12 billion active parameters. Cognition applies large-scale mid-training and reinforcement learning to improve the model's programming accuracy, reasoning capabilities, and ability to complete complex software engineering tasks. SWE-2 Flash supports code generation, repository maintenance, automated code reviews, feature implementation, documentation updates, and agent-driven software development. Its optimized architecture delivers approximately 200 tokens per second, making it three times faster than SWE-2 while operating at one-fifth the inference cost. The model achieved a score of 24.0% on FrontierCode 2.0, 45.5% on FrontierCode 1.1 Main, and 89.2% on Terminal-Bench 2.1 in Cognition's published evaluations. Training improvements also target general reasoning, problem-solving, and cybersecurity tasks to expand the range of activities supported by autonomous coding agents. SWE-2 Flash is available in Devin Desktop and CLI, allowing developers to incorporate the model into interactive and automated software engineering workflows. Cognition is also developing a controlled model-weight access program for trusted industry partners and researchers interested in fine-tuning, infrastructure control, and deployment in sensitive environments.
Pricing
Integrations
Company Details
Product Details
SWE-2 Flash Features and Options
SWE-2 Flash User Reviews
Write a Review-
Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Amazing fast coding model Date: Nov 04 2026
Summary: Overall, SWE-2 Flash feels like the everyday version of SWE-2. It is quick, cheap, and capable enough for a huge amount of real coding work without making every agent run feel expensive or slow.
Positive: This is the kind of model I would use all day for normal engineering work. It is fast enough that it does not feel like I am waiting on the model, but it is still strong enough for feature work, code review, docs, automations, and debugging. The speed is probably the biggest win. Cognition says it runs at around 200 tokens per second versus about 60 for SWE-2, and that difference matters a lot once an agent starts iterating through files and tools. The cost-performance balance is also really good. It is one-fifth the price of SWE-2, while scoring 45.5 on FrontierCode 1.1 Main, 60.1 on DeepSWE 1.1, and 89.9 on SWE-Bench Pro v2 Hard.
Negative: My main complaint is that it is not the model I would choose for the hardest repo-wide work. SWE-2 still has a noticeable edge on some tougher benchmarks, so I would move up when the task really needs it.
Read More...
- Previous
- You're on page 1
- Next