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DeepSeek vs Boundless
DeepSeek sells V4.1 Flash first party with off-peak discounts and data stored in China. Boundless serves it in the US or Europe at $0.20 in, $1.00 out.
By The Subconscious Team · Updated
DeepSeek vs Boundless: key differences
DeepSeek's V4.1 Flash has 1M context and 384K max output at $0.30 in and $1.20 out per million tokens at peak. Off-peak hours cost half that, $0.15 in and $0.60 out, and cache hits cost a few cents or less. Data on the hosted API is stored in China, and V4 Pro requests now route to V4.1 Flash. Boundless serves V4.1 Flash at $0.20 in and $1.00 out with cached input at $0.01, and DeepSeek V4.1 Flash 1017 at $0.24 in and $0.96 out, which Vercel measured at 342 tokens per second. It still lists DeepSeek V4 Pro at $1.04 in and $2.08 out and V4 Flash at $0.04 in and $0.21 out, all with 1M context.
DeepSeek is the pick for the lowest V4.1 Flash prices when work runs off-peak, which covers US business hours, and for reasoning effort controls. Boundless fits teams that need DeepSeek models served outside China with zero data retention, or that still want V4 Pro. Vetted security teams can also apply for an abliterated DeepSeek V4.1 Flash 1017 through its Defensive Access program.
What DeepSeek and Boundless do
DeepSeek
DeepSeek is the Chinese lab whose open-weight models reset price expectations for the whole market. Its main model is V4.1 Flash, with 1M context and 384K max output, which shipped September 10, 2026 with built-in image understanding at $0.30 in and $1.20 out at peak. DeepSeek is phasing out V4 Pro: since September 14, deepseek-v4-pro requests route to V4.1 Flash at Flash rates until V4.1 Pro launches. Cache hits cost a few cents per million or less, and the weights ship on Hugging Face under an MIT license.
Example models: DeepSeek V4.1 Flash
Full DeepSeek profileBoundless
Boundless launched in September 2026 as an inference partner for AI-native startups. It sells two things. The Model API serves pre-tuned models on shared capacity, billed per token from prepaid credits with a budget per API key. Tailored inference reserves capacity for one customer, and Boundless engineers pick the model on the customer’s own evals, tune precision, batching, caching, speculative decoding and parallelism, then run the deployment against uptime, throughput and latency targets written into the contract. A free two-week evaluation tests those targets on real traffic against the customer’s current provider first.
Example models: GLM-5.3, DeepSeek V4.1 Flash, Kimi K3
Full Boundless profileShould you choose DeepSeek or Boundless?
DeepSeek vs Boundless at a glance
| Attribute | DeepSeek | Boundless |
|---|---|---|
| Model access | Open weights (MIT) | Open weights, plus closed GPT and Claude |
| Flagship models | DeepSeek V4.1 Flash | GLM-5.3, DeepSeek V4.1 Flash, Kimi K3 |
| Speed | ~209 tok/s on V4.1 Flash | 342 tok/s on DeepSeek V4.1 Flash 1017 (Vercel) |
| Price | Off-peak hours at half price | $0.04–$2.30 in, $0.21–$11.40 out per 1M (open) |
| Customization | Open weights to fine-tune | Serving-stack tuning, no fine-tuning |
| Deployment | First-party API, Hugging Face weights | Serverless API, reserved tailored capacity |
| Long context | 1M, 384K max output | 1M context on most models |
Frequently asked questions
What is the difference between DeepSeek and Boundless?
DeepSeek sells V4.1 Flash first party with off-peak discounts and data stored in China. Boundless serves it in the US or Europe at $0.20 in, $1.00 out.
When should I choose DeepSeek over Boundless?
Off-peak V4.1 Flash at half price; Reasoning effort controls; MIT weights to self-host.
When should I choose Boundless over DeepSeek?
DeepSeek served outside China; DeepSeek V4 Pro still on offer; Abliterated V4.1 Flash for security teams.
Is DeepSeek or Boundless cheaper?
DeepSeek: Off-peak hours at half price. Boundless: $0.04–$2.30 in, $0.21–$11.40 out per 1M (open). The cheaper choice depends on the model and workload.
Which has more context, DeepSeek or Boundless?
DeepSeek: 1M, 384K max output. Boundless: 1M context on most models.
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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.