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Subconscious vs Groq
Groq is fast on short calls but caps near 131K context. Subconscious keeps agents fast past 200K tokens and into the millions, with a 5M+ effective context.
By The Subconscious Team · Updated
Subconscious vs Groq: key differences
Groq and Subconscious are both speed plays, aimed at different request shapes. Groq's LPU keeps weights in on-chip SRAM and publishes 500 to 1,000 tokens per second on GPT-OSS models, with tight tail latency. Its catalog, though, caps around 131K context. A coding agent that has been running for a while passes that limit and cannot continue on Groq without trimming its history. Subconscious starts roughly where that ceiling sits. It delivers a 5M+ effective context window from KV cache pruning and 2x faster task completion, and it bills on processed tokens, so the long trace stays both fast and affordable.
For voice agents and multi-call loops where each step is short and has to come back fast, Groq is the better tool, and its small-model prices sit near the market floor. The open questions sit on Groq's side for long-term bets: the catalog is shrinking after Llama 3.3 70B and Llama 3.1 8B shut down, it hosts no fine-tuned models, and most of its engineers now work at NVIDIA. Subconscious adds dedicated and on-prem options that can run nearly any open model.
What Subconscious and Groq do
Subconscious
Subconscious is an MIT CSAIL spinout in Kendall Square that builds inference for long-horizon agents, the workloads where a single trace runs past 200K tokens and often into the millions. Its runtime drops in as a replacement for vLLM or SGLang. Instead of rereading an ever-growing context on every step, it prunes the KV cache and preserves suffix state, and Subconscious co-designs the runtime with post-trained model variants it calls Marathon. Against open models on standard inference, Subconscious delivers 2x faster task completion, delivers a 5M+ effective context window, cuts cost 50% and up to 80%, and scores neutral to 10% better on agentic benchmarks.
Example models: GLM 5.3, DeepSeek V4.1 Flash
Full Subconscious profileGroq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profileShould you choose Subconscious or Groq?
Subconscious
Choose Subconscious for
- Traces that outgrow Groq's roughly 131K context cap
- Long coding sessions billed on processed tokens
- Dedicated or on-prem serving of open models
Groq
Choose Groq for
- Voice agents where every pause is noticeable
- Short agent steps that need tight tail latency
- Cheap per-token calls on small open models
Subconscious vs Groq at a glance
| Attribute | Subconscious | Groq |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GLM 5.3, DeepSeek V4.1 Flash | GPT-OSS 120B, Qwen 3.6 27B |
| Speed | 2x faster task completion | 500–1,000 tok/s |
| Price | 50–80% lower cost; billed on processed tokens | Near the floor on small models |
| Customization | Marathon post-trained variants | No fine-tuned model hosting |
| Deployment | Managed API, dedicated, on-prem | GroqCloud API |
| Long context | 5M+ effective context | Around 131K max |
Frequently asked questions
What is the difference between Subconscious and Groq?
Groq is fast on short calls but caps near 131K context. Subconscious keeps agents fast past 200K tokens and into the millions, with a 5M+ effective context.
When should I choose Subconscious over Groq?
Traces that outgrow Groq's roughly 131K context cap; Long coding sessions billed on processed tokens; Dedicated or on-prem serving of open models.
When should I choose Groq over Subconscious?
Voice agents where every pause is noticeable; Short agent steps that need tight tail latency; Cheap per-token calls on small open models.
Is Subconscious or Groq cheaper?
Subconscious: 50–80% lower cost; billed on processed tokens. Groq: Near the floor on small models. The cheaper choice depends on the model and workload.
Which has more context, Subconscious or Groq?
Subconscious: 5M+ effective context. Groq: Around 131K max.
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Run your longest agent traces on Subconscious
Point the OpenAI or Anthropic SDK, or the coding agent you already use, at Subconscious. Keep Groq for the work it does best and send the long runs to us.