AutoGen vs Together AI
Side-by-side trajectory, velocity, and editorial themes.
AutoGen has gone quiet — last release was September 2025, with no public update for nearly eight months.
AutoGen's most recent release is python-v0.7.5 on 2025-09-30. The last sustained activity came in a Q3 2025 cluster: v0.7.0 through v0.7.5, with v0.7.1 introducing nested Teams as group-chat participants, RedisMemory, latest MCP version, and OpenAIAgent built-in tools. v0.7.2 made DockerCommandLineCodeExecutor the default for MagenticOne and added an approval_func to CodeExecutorAgent. After that, the cadence stops cold — eight months of public silence as of May 2026.
The technical arc through July–September 2025 was clear: deeper team composition (teams-as-tools, teams-as-participants), better memory (RedisMemory, GraphFlow state retention across resumes), and an MCP-aligned tool surface. Then nothing. For a Microsoft research project in the agent-framework space, an eight-month gap during the most competitive period in agent tooling (LangGraph, OpenAI Agents SDK, Anthropic's Claude Agent SDK, Semantic Kernel agent expansions) is not normal silence — the absence is the signal. Without a release or public roadmap statement, this reads as either pre-major-rewrite mode or quiet wind-down/absorption into another Microsoft framework.
If there is no release within the next quarter, treat AutoGen as effectively frozen for production use; the agentic framework ecosystem has moved without it. If a release does land, expect it to be a structural rewrite tied to Semantic Kernel or a Microsoft-wide agent surface rather than continuation of the 0.7.x line.
Together AI is pricing itself as the open-stack alternative to frontier coding-agent APIs.
Together is hammering on two things: (a) inference economics, with a benchmark claiming 76% lower cost than Claude Opus 4.6 on coding-agent workloads, and (b) breadth of model surface, evidenced by day-0 Nemotron 3 Nano Omni, DeepSeek-V4 Pro at 512K context, and Goose-driven 'deploy any HuggingFace model' tooling. Side outputs — a voice finder, the Violin video-translation tool, and a Pearl Research Labs crypto-inference partnership — broaden the developer surface without changing the core narrative.
Together is positioning to be the default API for teams running coding agents on open models, with explicit price/perf comparisons against closed labs. The pattern of day-0 launches plus dedicated container offerings makes the strategy clear: any open frontier model should be one click away on Together. Crypto-adjacent and partnership work (Pearl, Adaption) reads as experimentation rather than core roadmap.
Expect more cost-comparison content against named frontier APIs and a tighter coding-agent SKU (likely a benchmark-grounded preset for Cursor/Aider-style workloads). Day-0 launch cadence will continue as the differentiator versus AWS Bedrock and other neoclouds.
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