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Subconscious vs Cerebras
Cerebras speeds up decoding. Subconscious speeds up the real bottleneck of long agents, the growing context, with 2x faster task completion on traces past 200K tokens.
By The Subconscious Team · Updated
Subconscious vs Cerebras: key differences
Cerebras sells decode speed. Its wafer-scale chip runs GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out, about six times Groq on the same weights. That pays off when generation is the wait, as in voice, live autocomplete and long outputs. It helps less on long agent loops, where the cost is rereading an ever-larger context on every step, and the speed does little when an agent mostly waits on tools or hidden reasoning. Subconscious targets that cost. It prunes the KV cache so each step processes less, cuts cost 50% to 80% versus open models on standard inference, delivers a 5M+ effective context window, and bills only processed tokens.
Both catalogs are small, but they are shaped differently. Cerebras's shared API lists GPT-OSS 120B and Gemma 4 31B, with more models behind a sales conversation or partners like OpenRouter. Subconscious serves GLM 5.3 and DeepSeek V4.1 Flash, with dedicated or on-prem runs of nearly any open model. Cerebras also offers the only wafer-scale route to a closed frontier model, through OpenAI's Ultrafast preview of GPT-5.6 Sol. Streaming UIs and output-heavy steps belong on Cerebras. When the context, not the output, is what keeps growing, Subconscious is the better match.
What Subconscious and Cerebras 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 profileCerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Gemma 4 31B as of August 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Gemma 4 31B
Full Cerebras profileShould you choose Subconscious or Cerebras?
Subconscious
Choose Subconscious for
- Agent loops where rereading context, not decoding, dominates cost
- Traces past 200K tokens on GLM 5.3 or DeepSeek V4.1 Flash
- Long runs billed on processed tokens after compression
Cerebras
Choose Cerebras for
- Streaming UIs and voice where generation speed is the wait
- Output-heavy agent steps on GPT-OSS 120B
- Wafer-scale speed on GPT-5.6 Sol through OpenAI's preview
Subconscious vs Cerebras at a glance
| Attribute | Subconscious | Cerebras |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GLM 5.3, DeepSeek V4.1 Flash | GPT-OSS 120B, Gemma 4 31B |
| Speed | 2x faster task completion | ~3,000 tok/s on GPT-OSS 120B |
| Price | 50–80% lower cost; billed on processed tokens | $0.35 in, $0.75 out (GPT-OSS 120B) |
| Customization | Marathon post-trained variants | Unknown |
| Deployment | Managed API, dedicated, on-prem | Shared API, dedicated, partners |
| Long context | 5M+ effective context | Unknown |
Frequently asked questions
What is the difference between Subconscious and Cerebras?
Cerebras speeds up decoding. Subconscious speeds up the real bottleneck of long agents, the growing context, with 2x faster task completion on traces past 200K tokens.
When should I choose Subconscious over Cerebras?
Agent loops where rereading context, not decoding, dominates cost; Traces past 200K tokens on GLM 5.3 or DeepSeek V4.1 Flash; Long runs billed on processed tokens after compression.
When should I choose Cerebras over Subconscious?
Streaming UIs and voice where generation speed is the wait; Output-heavy agent steps on GPT-OSS 120B; Wafer-scale speed on GPT-5.6 Sol through OpenAI's preview.
Is Subconscious or Cerebras cheaper?
Subconscious: 50–80% lower cost; billed on processed tokens. Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.
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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 Cerebras for the work it does best and send the long runs to us.