AkashML
Explore AkashML models on TrustedRouter with current routes, token pricing, policy sources, privacy posture, regional availability, and API support.
AkashMLakashml
No provider claim
These privacy labels describe AkashML, the upstream model provider. ZDR is a retention policy; verified confidential inference additionally requires attested provider compute and end-to-end encryption.
| Provider | AkashML |
|---|---|
| Routing status | Active |
| Provider website | https://akashml.com/ |
| Models | 6 public models |
| Credits routes | 6 |
| Zero data retention | not claimed |
| Verified confidential inference | Not verified |
| Policy note | No contractual zero-retention, confidential-compute, or E2EE claim is tracked for TrustedRouter's AkashML account. This route is Standard. Policy source |
Measured performance
20 samplesContinuously sampled across AkashML'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 | 2017 ms |
|---|---|
| Effective throughput | — |
| Uptime | 100.00% |
| Model | p50 TTFT | Effective throughput | Uptime | Config excluded | Availability samples |
|---|---|---|---|---|---|
| meta-llama/llama-3.3-70b-instruct | 1394 ms | — | 100.00% | — | 1 |
| z-ai/glm-5.3 | 1417 ms | — | 100.00% | — | 4 |
| qwen/qwen3.8-27b | 1421 ms | — | 100.00% | — | 2 |
| qwen/qwen3.6-35b-a3b | 2017 ms | — | 100.00% | — | 5 |
| openai/gpt-oss-20b | 2265 ms | — | 100.00% | — | 3 |
| openai/gpt-oss-120b | 2421 ms | — | 100.00% | — | 5 |
AkashML performance history · Full provider & model leaderboard.
Models served by AkashML.
Each row links to pricing, provider, benchmark, and API pages for the model.
| Model | AI IQ | Context | Input | Cached input | Output |
|---|---|---|---|---|---|
meta-llama/llama-3.3-70b-instructMeta: Llama 3.3 70B Instruct |
— | 131,072 | $0.211/1M | $0.1055/1M | $0.5486/1M |
openai/gpt-oss-120bOpenAI: gpt-oss-120b |
IQ 98#99 | 131,072 | $0.03165/1M | $0.03165/1M | $0.17935/1M |
openai/gpt-oss-20bOpenAI: gpt-oss-20b |
IQ 93#113 | 131,072 | $0.0211/1M | Not published | $0.1055/1M |
qwen/qwen3.6-35b-a3bQwen: Qwen3.6 35B A3B |
IQ 100#94 | 262,144 | $0.1055/1M | $0.05275/1M | $0.9495/1M |
qwen/qwen3.8-27bQwen: Qwen3.8 27B |
IQ 110#60 | 262,144 | $0.26375/1M | $0.05275/1M | $2.321/1M |
z-ai/glm-5.3Z.ai: GLM 5.3 |
IQ 123#18 | 1,048,576 | $1.3715/1M | $0.2743/1M | $4.642/1M |
Questions
Does AkashML have zero data retention?
TrustedRouter does not currently mark AkashML 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 AkashML end-to-end encrypted?
TrustedRouter does not currently mark AkashML 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 AkashML models are available through TrustedRouter?
This page currently lists 6 public AkashML models, with live pricing, route count, context length, measured performance when available, and links to each model's provider and benchmark pages.