GLM 5.3Morph0.046 / 4.16 GLM 5.3Decart0.85 / 2.68 GLM 5.3Inceptron0.50 / 0.52 GLM 5.3Baidu0.17 / 0.52 GLM 5.3Wafer0.066 / 4.00 GLM 5.3Wafer0.14 / 4.00 GLM 5.3Io Net0.41 / 2.42 GLM 5.3Tenstorrent0.50 / 2.08 GLM 5.3InferenceNet0.067 / 3.67 Claude Sonnet 5.5Claude Platform on AWS1.67 / 8.33 Claude Sonnet 5.5Google1.67 / 8.33 Claude Sonnet 5.5Azure1.83 / 9.16 Claude Sonnet 5.5Amazon Bedrock1.67 / 8.33 Claude Sonnet 5.5Azure1.67 / 8.33 Claude Sonnet 5.5Google1.83 / 9.16 Claude Sonnet 5.5Google1.83 / 9.16 Claude Sonnet 5.5Anthropic1.67 / 8.33 Mimo V2.6 ProDeepInfra0.36 / 0.73 GPT 5.6 SolOpenAI0.83 / 4.16 GPT 6.1 SolOpenAI0.83 / 4.16 GPT 6 SolOpenAI0.83 / 4.16 Grok 4.7xAI1.67 / 5.00 Claude Opus 5.5Anthropic3.33 / 16.66 Claude Opus 5Claude Platform on AWS4.16 / 20.82 GPT 6 AstraOpenAI4.16 / 20.82 Claude Fable 5.1Amazon Bedrock8.33 / 41.64 Claude Fable 5Claude Platform on AWS8.33 / 41.64 GLM 5.3Morph0.046 / 4.16 GLM 5.3Decart0.85 / 2.68 GLM 5.3Inceptron0.50 / 0.52 GLM 5.3Baidu0.17 / 0.52 GLM 5.3Wafer0.066 / 4.00 GLM 5.3Wafer0.14 / 4.00 GLM 5.3Io Net0.41 / 2.42 GLM 5.3Tenstorrent0.50 / 2.08 GLM 5.3InferenceNet0.067 / 3.67 Claude Sonnet 5.5Claude Platform on AWS1.67 / 8.33 Claude Sonnet 5.5Google1.67 / 8.33 Claude Sonnet 5.5Azure1.83 / 9.16 Claude Sonnet 5.5Amazon Bedrock1.67 / 8.33 Claude Sonnet 5.5Azure1.67 / 8.33 Claude Sonnet 5.5Google1.83 / 9.16 Claude Sonnet 5.5Google1.83 / 9.16 Claude Sonnet 5.5Anthropic1.67 / 8.33 Mimo V2.6 ProDeepInfra0.36 / 0.73 GPT 5.6 SolOpenAI0.83 / 4.16 GPT 6.1 SolOpenAI0.83 / 4.16 GPT 6 SolOpenAI0.83 / 4.16 Grok 4.7xAI1.67 / 5.00 Claude Opus 5.5Anthropic3.33 / 16.66 Claude Opus 5Claude Platform on AWS4.16 / 20.82 GPT 6 AstraOpenAI4.16 / 20.82 Claude Fable 5.1Amazon Bedrock8.33 / 41.64 Claude Fable 5Claude Platform on AWS8.33 / 41.64
Swiss Dedicated Model Usage data Deutsch

AstrionCore · compute made to measure

Compute, measured, not promised.

LLMs, model evaluation, dedicated inference, FPGA analytics and reservoir computing — one place to start. Every offer shows honestly where it stands, and every number how we measured it.

Compute hall with server towers, an FPGA grid and glowing atoms connected by beams of light
6offers from LLMs to quantum reservoirs
1available today, the rest as pilot or in development
5measured results on this page
CHoperated by AstrionCore in Switzerland

Offers

What you can use today is marked “Available”. Pilots run on our side and we open them one by one; “In development” is the target — we already take requests for it.

LLM compute

Available

Any LLM through one API, at the lowest price that reaches your measured quality bar.

CHF per 1M tokens, daily price
  • OpenAI-compatible API, one key for all platforms
  • Quality tiers per use case instead of a model lottery (model taylor)
  • Live price comparison across platforms, card payment only
measured300 offers, 215 models, 3 price sources in the price book

Model evaluation

Pilot – on request

We measure your model or endpoint with open benchmarks, reproducibly and with evidence.

Fixed price per evaluation run
  • Compact suite (coding, knowledge, maths, instruction following) from a few francs
  • Every number with run ID, sample size and settings
  • Before/after for quantisation, fine-tuning or a change of provider
measuredCompact suite ≈ CHF 2 per offer for third-party models

Dedicated inference

In development

Reserved throughput on open models in Switzerland, no shared queue.

CHF per month and reserved capacity
  • Open weights (27B class, embeddings), fixed capacity
  • Data stays in Switzerland, no training on customer data
  • Tokens per second as a commitment, measured and published
measured27B NVFP4 on RTX 5090: 72–81 tokens/s per request, 573 tokens/s at 8 parallel

FPGA streaming analytics

Pilot – on request

Features from data streams computed in hardware, bit-exact, at sub-millisecond cadence.

Pilot, fixed price per stream and month
  • Dedicated feature engine on FPGA, checked bit-identical against its software twin
  • For market, sensor and telemetry streams
  • Raw data, features and checksums per event
measured3.27M events, 0 lost, 0 deviations from the twin; round trip p99 0.88 ms

FPGA dynamics computing

In development

Cellular automata, stencils, Ising/MaxCut directly as a circuit, not as a program on a GPU.

Job, price per run
  • One update per cell and clock cycle, all cells in parallel
  • Dynamics compiler: from model to circuit, bit-exact to the reference
  • Results with a check word from the chip
measuredBit-identical to the reference on silicon (Rule 110, GKL majority)
projection (place-and-route)Rule 110 N 4,096: computed ≈ 8× the best GPU (from place-and-route, not measured on the chip)

Reservoir & quantum reservoir computing

In development

Time-series forecasting with physical reservoirs, classical and as a Rydberg quantum simulation.

Study at a fixed price
  • Studies on memory, forecasting and chaotic time series
  • Honest comparison against tuned classical baselines
  • Later: runs on neutral-atom hardware
simulationOwn Lindblad simulator for 8–9 Rydberg atoms; no advantage over tuned ESNs measured so far

How we measure

So that nothing on this page claims more than operations can deliver.

Our own measurements

Performance numbers come from our own runs on open benchmarks, with the same settings for everyone. Third-party values are only used for pre-selection.

Kind of number

Every number says whether it was measured, projected from place-and-route or simulated. We claim no advantage we have not seen on the hardware.

Status shown

“Available” means: payable and usable today. Everything else is marked as pilot or in development.

Request a pilot

Tell us briefly what you need — we will get back to you. No payment, no commitment.