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Together AI vs General Compute
Together AI is the broadest open-model platform on GPUs. General Compute serves a short list of open models with decode on ASICs.
By The Subconscious Team · Updated
Together AI vs General Compute: key differences
Together AI puts serverless, batch, dedicated and raw GPU clusters on one bill, with 30+ open text models including GLM 5.3, DeepSeek V4.1 Flash and Kimi K3, context up to 512K and fine-tuning from LoRA to full SFT. General Compute serves four older open models, MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and GPT-OSS 120B, from $0.21 in and $0.38 out per million tokens. It pairs GPU prefill with ASIC decode and reports over 1,000 tokens per second on GPT-OSS 120B in its own benchmark.
Together is the pick for teams that want new open models within days, training and serving in one place, or GPU clusters. General Compute fits workloads where decode speed matters more than model choice. Both serve custom fine-tunes, and General Compute takes LoRA or full checkpoints trained elsewhere behind a private model ID.
What Together AI and General Compute do
Together AI
Together AI is the broadest open-model platform in the category. One bill covers per-token serverless inference, batch at up to 50% off, provisioned throughput with a 99% SLA, dedicated deployments, raw GPU clusters, managed fine-tuning and code sandboxes for agents. The text catalog runs past thirty open models, including GLM 5.3, DeepSeek V4.1 Flash, DeepSeek V4 Pro 0813, Kimi K3, Qwen 3.8 and MiniMax M3, plus image, video, speech and embedding models. Token prices sit at parity with Fireworks and Baseten.
Example models: Kimi K3, GLM 5.3, DeepSeek V4.1 Flash
Full Together AI profile
General Compute
General Compute is a San Francisco inference cloud built on alternative chips. It splits each request across hardware, with NVIDIA GPUs handling prefill and ASICs from Cerebras, SambaNova, Positron AI and d-Matrix handling decode. In its own open benchmark on GPT-OSS 120B it measured 1,025 to 1,234 output tokens per second against 100 to 121 on an unnamed GPU cloud, and up to 16.2x faster end to end. Founders Finn Puklowski and Jason Goodison raised a $15M seed led by FUSE, an up to $400M debt facility from Upper90 and, on October 27, 2026, a $100M Series A co-led by Blackbird and Abstract.
Example models: MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Full General Compute profileShould you choose Together AI or General Compute?
Together AI
Choose Together AI for
- Broad, current open-model catalog
- Fine-tuning and RL, then serving
- Reserved GPU clusters
General Compute
Choose General Compute for
- Fast decode on a short model list
- Custom checkpoints on ASIC hardware
- Tokens-per-second SLAs
Together AI vs General Compute at a glance
| Attribute | Together AI |  General Compute |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | Kimi K3, GLM 5.3, DeepSeek V4.1 Flash, Qwen 3.8 | MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B |
| Speed | 0.99s TTFT on DeepSeek V4 Pro | 1,000+ tok/s on GPT-OSS 120B (vendor) |
| Price | Parity with Fireworks and Baseten | $0.21–$0.28 in, $0.38–$1.20 out per 1M |
| Customization | LoRA and full SFT; RL in beta | Custom LoRA and fine-tuned checkpoints |
| Deployment | Serverless, dedicated, GPU clusters | Serverless API, dedicated racks, bare metal |
| Long context | 512K on DeepSeek V4 Pro 0813 | 192K (MiniMax M2.7) |
Frequently asked questions
What is the difference between Together AI and General Compute?
Together AI is the broadest open-model platform on GPUs. General Compute serves a short list of open models with decode on ASICs.
When should I choose Together AI over General Compute?
Broad, current open-model catalog; Fine-tuning and RL, then serving; Reserved GPU clusters.
When should I choose General Compute over Together AI?
Fast decode on a short model list; Custom checkpoints on ASIC hardware; Tokens-per-second SLAs.
Is Together AI or General Compute cheaper?
Together AI: Parity with Fireworks and Baseten. General Compute: $0.21–$0.28 in, $0.38–$1.20 out per 1M. The cheaper choice depends on the model and workload.
Which has more context, Together AI or General Compute?
Together AI: 512K on DeepSeek V4 Pro 0813. General Compute: 192K (MiniMax M2.7).
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Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.