DigitalOcean Gradient AI
Explore DigitalOcean Gradient AI models on TrustedRouter with current routes, token pricing, policy sources, privacy posture, regional availability, and API support.
DigitalOcean Gradient AIdigitalocean
No provider claim
| Provider | DigitalOcean Gradient AI |
|---|---|
| Routing status | Active |
| Provider website | https://www.digitalocean.com/products/gradient-ai-platform |
| Models | 18 public models |
| Credits routes | 18 |
| Zero data retention | not claimed |
| Confidential compute | not claimed |
| Provider E2EE | not claimed |
| Policy note | No provider-ZDR claim is tracked here. DigitalOcean's Gradient AI model and pricing documentation is linked for data-handling review. Policy source |
Measured performance
34 samplesContinuously sampled across DigitalOcean Gradient AI's routed models: p50 TTFT, effective throughput, and success rate. Effective throughput uses provider-reported output tokens over complete request time. Unsupported route and probe-configuration rows are separated from provider downtime. No prompt or output content stored.
| p50 TTFT | 2136 ms |
|---|---|
| Effective throughput | 35 tok/s n=8 |
| Uptime | 100.00% |
| Model | p50 TTFT | Effective throughput | Uptime | Config excluded | Availability samples |
|---|---|---|---|---|---|
| minimax/minimax-m2.5 | 1021 ms | — | 100.00% | — | 1 |
| mistralai/ministral-3-14b-instruct | 1090 ms | — | 100.00% | — | 2 |
| moonshotai/kimi-k2.6 | 1103 ms | 39 tok/s n=2 | 100.00% | — | 1 |
| nvidia/nemotron-3-ultra-550b | 1108 ms | — | 100.00% | — | 2 |
| nvidia/nemotron-nano-12b-v2-vl | 1141 ms | — | 100.00% | — | 2 |
| z-ai/glm-5.1 | 1196 ms | — | 100.00% | — | 1 |
| deepseek/deepseek-v4-pro | 1302 ms | — | 100.00% | — | 1 |
| meta-llama/llama-4-maverick | 1424 ms | — | 100.00% | — | 4 |
| google/gemma-4-31b-it | 1485 ms | 72 tok/s n=2 | 100.00% | — | 1 |
| xiaomi/mimo-v2.5-pro | 2136 ms | 31 tok/s n=1 | 100.00% | — | 2 |
| qwen/qwen3.5-397b-a17b | 2161 ms | — | 100.00% | — | 3 |
| nvidia/nemotron-3-nano-omni | 2692 ms | — | 100.00% | — | 2 |
| deepseek/deepseek-v4-flash | 2965 ms | 7 tok/s n=2 | 100.00% | — | 5 |
| nvidia/nemotron-3-super-120b | 3019 ms | — | 100.00% | — | 3 |
| moonshotai/kimi-k2.5 | 3125 ms | — | 100.00% | — | 1 |
| deepseek/deepseek-v3.2 | 3204 ms | — | 100.00% | — | 3 |
| z-ai/glm-5.2 | — | 12 tok/s n=1 | — | — | 0 |
DigitalOcean Gradient AI performance history · Full provider & model leaderboard.
Models served by DigitalOcean Gradient AI.
Each row links to pricing, provider, benchmark, and API pages for the model.
| Model | AI IQ | Context | Input | Cached input | Output |
|---|---|---|---|---|---|
deepseek/deepseek-v3.2DeepSeek: DeepSeek V3.2 |
IQ 103#74 | 163,840 | $0.26375/1M | $0.079125/1M | $0.844/1M |
deepseek/deepseek-v4-flashDeepSeek: DeepSeek V4 Flash 0423 |
IQ 113#46 | 1,024,000 | $0.07174/1M | $0.017935/1M | $0.17724/1M |
deepseek/deepseek-v4-proDeepSeek: DeepSeek V4 Pro 0423 |
IQ 117#36 | 1,024,000 | $0.91785/1M | $0.18357/1M | $1.8357/1M |
google/gemma-4-31b-itGoogle: Gemma 4 31B |
IQ 101#83 | 262,144 | $0.1899/1M | $0.03798/1M | $0.5275/1M |
meta-llama/llama-4-maverickMeta: Llama 4 Maverick |
IQ 90#114 | 128,000 | $0.211/1M | Not published | $0.73428/1M |
minimax/minimax-m2.5MiniMax: MiniMax M2.5 |
IQ 105#72 | 200,000 | $0.3165/1M | $0.0633/1M | $1.266/1M |
mistralai/ministral-3-14b-instructMinistral 3 14B Instruct |
— | 262,144 | $0.211/1M | Not published | $0.211/1M |
moonshotai/kimi-k2.5MoonshotAI: Kimi K2.5 |
IQ 111#55 | 262,144 | $0.5275/1M | $0.214165/1M | $2.8485/1M |
moonshotai/kimi-k2.6MoonshotAI: Kimi K2.6 |
IQ 119#30 | 262,144 | $1.00225/1M | $0.20045/1M | $4.22/1M |
nvidia/nemotron-3-nano-omniNemotron Nano 3 Omni |
— | 65,536 | $0.5275/1M | Not published | $0.9495/1M |
nvidia/nemotron-3-super-120bNemotron-3-Super-120B |
— | 1,000,000 | $0.3165/1M | $0.0633/1M | $0.68575/1M |
nvidia/nemotron-3-ultra-550bNemotron 3 Ultra |
— | 131,072 | $0.9495/1M | Not published | $1.7935/1M |
nvidia/nemotron-nano-12b-v2-vlNemotron Nano 12B v2 VL |
— | 128,000 | $0.211/1M | Not published | $0.633/1M |
qwen/qwen3.5-397b-a17bQwen: Qwen3.5 397B A17B |
— | 262,144 | $0.58025/1M | $0.117105/1M | $3.6925/1M |
xiaomi/mimo-v2.5-proXiaomi: MiMo-V2.5-Pro |
IQ 116#39 | 1,048,576 | $0.422/1M | $0.0844/1M | $1.5825/1M |
z-ai/glm-5Z.ai: GLM 5 |
IQ 105#69 | 198,000 | $1.055/1M | $0.211/1M | $3.376/1M |
z-ai/glm-5.1Z.ai: GLM 5.1 |
IQ 114#43 | 200,000 | $1.3715/1M | $0.2743/1M | $4.5365/1M |
z-ai/glm-5.2Z.ai: GLM 5.2 |
IQ 120#27 | 1,048,576 | $0.7385/1M | $0.110775/1M | $2.321/1M |
Questions
Does DigitalOcean Gradient AI have zero data retention?
TrustedRouter does not currently mark DigitalOcean Gradient AI as provider-level zero data retention. Use trustedrouter/zdr or provider.min_privacy=zdr to select a different eligible route, and review the linked policy source for changes.
Is DigitalOcean Gradient AI end-to-end encrypted?
TrustedRouter does not currently mark DigitalOcean Gradient AI as end-to-end encrypted at the provider boundary. The TrustedRouter gateway is still attested, but the selected provider normally receives the request in order to run the model. Use trustedrouter/e2e for the stronger route requirement.
Which DigitalOcean Gradient AI models are available through TrustedRouter?
This page currently lists 18 public DigitalOcean Gradient AI models, with live pricing, route count, context length, measured performance when available, and links to each model's provider and benchmark pages.