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RunInfra vs Boundless
RunInfra sells five open models, $10 coding plans and an agent that builds deployments. Boundless has a larger catalog and engineers who run reserved capacity.
By The Subconscious Team · Updated
RunInfra vs Boundless: key differences
RunInfra's hosted library has five open models behind one key for the OpenAI and Anthropic SDKs, from Nemotron 3.5 Lightning 30B at $0.05 in and $0.15 out per million tokens to DeepSeek V4.1 Flash at $0.14 in and $0.58 out. Coding plans start at $10 a month, and its deployment agent benchmarks GPUs, tries quantized variants and ships endpoints that scale to zero. Boundless lists 22 models, including GPT and Claude, and charges $0.20 in and $1.00 out for DeepSeek V4.1 Flash. Its tailored inference has Boundless engineers tune and operate reserved capacity against uptime, throughput and latency targets in the contract.
Pick RunInfra for the lower DeepSeek V4.1 Flash price, a flat-rate plan in Claude Code or Codex, or a self-serve endpoint for a model you upload. Pick Boundless for larger models like GLM-5.3 and Kimi K3, closed models on the same key, or a deployment someone else tunes and runs.
What RunInfra and Boundless do
RunInfra
RunInfra pitches open models built for agents, with two ways in. Its hosted Model APIs serve a five-model library, including Nemotron 3.5 Lightning 30B, Qwen 3.8 27B, Ornith 1.5 35B, GLM 5.3 Flash and DeepSeek V4.1 Flash, behind one key that works with both the OpenAI and Anthropic SDKs. Prices run from $0.05 in and $0.15 out on Nemotron to $0.14 in and $0.58 out on DeepSeek V4.1 Flash, and cached input starts at $0.01. Coding plans start at $10 a month with limits that reset every five hours and every week, and they plug into Claude Code, Codex, OpenCode, Cline, Aider and dozens of other agent CLIs.
Example models: Nemotron 3.5 Lightning 30B, Qwen 3.8 27B
Full RunInfra 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 RunInfra or Boundless?
RunInfra vs Boundless at a glance
| Attribute | RunInfra | Boundless |
|---|---|---|
| Model access | Open weights | Open weights, plus closed GPT and Claude |
| Flagship models | Nemotron 3.5 Lightning 30B, Qwen 3.8 27B | GLM-5.3, DeepSeek V4.1 Flash, Kimi K3 |
| Speed | ~541 tok/s on Nemotron 3.5 Lightning 30B (vendor); cold starts under 2s | 342 tok/s on DeepSeek V4.1 Flash 1017 (Vercel) |
| Price | From $0.05 in, $0.15 out; coding plans from $10 a month | $0.04–$2.30 in, $0.21–$11.40 out per 1M (open) |
| Customization | Uploads up to 50 GB; auto-quantization | Serving-stack tuning, no fine-tuning |
| Deployment | Model APIs, agent-built endpoints | Serverless API, reserved tailored capacity |
| Long context | Varies by model | 1M context on most models |
Frequently asked questions
What is the difference between RunInfra and Boundless?
RunInfra sells five open models, $10 coding plans and an agent that builds deployments. Boundless has a larger catalog and engineers who run reserved capacity.
When should I choose RunInfra over Boundless?
Coding plans from $10 a month; Cheaper DeepSeek V4.1 Flash; Self-serve endpoints for uploaded models.
When should I choose Boundless over RunInfra?
Larger open models like Kimi K3; Open and closed models on one key; Managed reserved capacity.
Is RunInfra or Boundless cheaper?
RunInfra: From $0.05 in, $0.15 out; coding plans from $10 a month. 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, RunInfra or Boundless?
RunInfra: Varies by model. Boundless: 1M context on most models.
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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.