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Model infoModelsSnapshot: 15 Oct 2026

Sophea AI · KIEFER SA / Sophea ASR K1

Sophea ASR K1 · September revision

Historical two-model system using learned per-clip selection between a far-field Qwen adaptation and a Greek-adapted Canary model. Current October API behavior is recorded separately.

historicalClosed weightsSpeech recognition
Official documentation (opens in a new tab)Reviewed 13 Oct 2026
6 of 16 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedKIEFER SA · paper-documented system
Output billingNot collectedNo inferred price

Specifications

Provider-documented facts. “Not collected” means we have not verified that field yet, not that the feature is unsupported.

Context / input limit
Not collected
Maximum output
Not collected
Reasoning
Not collected
Tool calling
Not collected
Structured output
Not collected
Streaming
Not supportedSource for Streaming (opens in a new tab)

Paper explicitly uses the standalone far-field Qwen variant for interactive realtime traffic instead of the combined arbiter.

Batch processing
SupportedSource for Batch processing (opens in a new tab)

Paper describes offline batch role for the combined system.

Fine-tuning
Not collected
Knowledge cutoff
Not collected
Release date
Not collected
Parameters
Not collected
Architecture
Gradient-boosted per-clip arbiter over two ASR models, selecting one complete hypothesis rather than voting word by wordSource for Architecture (opens in a new tab)

Features include confidences, speech presence, duration, word rate, length ratio and cross-model agreement; hard rejection rules precede routing.

Languages
English, GreekSource for Languages (opens in a new tab)

Arbiter calibrated on English development pools. Greek uses the far-field Qwen leg alone with forced-language decoding.

Context caching
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Access & pricing

Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.

KIEFER SA · paper-documented system

Provider source (opens in a new tab)
API model ID
Not collected

No public immutable checkpoint selector or standalone API contract verified for this dated/internal system.

Access
Historical API-served preview described in the September paper. Current base selector has changed internally; separate access to this revision is unverified.
Regions
Original experimental deployment location not specified

Endpoint pricing has not been collected. Check the provider for applicable rates.

Data & enterprise terms

The paper releases no model weights, data or internal tooling. No standalone processing agreement or data-retention contract is established for this paper-only/datetime-specific record; current preview policies are not backfilled.

Read the service policy (opens in a new tab)

Caching

Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.

01 / INITIAL INPUTProcess & retain

The system processes eligible input and retains reusable state.

02 / LATER REQUESTCheck available state

Reuse depends on matching input, session state and the cache policy.

03 / CACHE HITReuse & generate

Reusing state can reduce repeated work. Any charges follow the billing rules below.

KIEFER SA · paper-documented system

Not verified

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

How it works
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Minimum reusable input
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Lifetime & refresh
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

How to enable it
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Usage fields
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Billing rules
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

Limits & data boundaries
Not collected

No model-specific prompt-cache contract verified. Server-side audio segmentation, speech buffers and reused decoders do not establish discounted token caching.

No verified cache rate for this endpoint. An empty rate is not a zero charge.

What the measurements say

September paper · seven cleaned English datasets

KIEFER SA / Sophea authors · provider-reported
4.35% WER

Table 4 mean under forced-English decoding; AMI close-talk, Earnings22 cleaned AA chunked, Gigaspeech cleaned, LS clean/other, SPGISpeech and VoxPopuli clean-accent. Single-run results with no confidence interval; acknowledged Canary AMI training exposure.

Evaluation source (opens in a new tab)

September API · Greek noisy environment

KIEFER SA / Sophea authors · provider-reported
25.88% WER

Provider private data, far-field Qwen leg only; forced Greek. Reported 95% CI 24.44–27.19. 24 concurrent clients on one B200 is evaluation setup, not a public account quota.

Evaluation source (opens in a new tab)

September API · English noisy environment

KIEFER SA / Sophea authors · provider-reported
14.21% WER

Provider private data; arbiter routed 52 of 719 clips to Canary. Reported 95% CI 13.01–15.57; separate re-decode scored 14.15. Not current October model performance.

Evaluation source (opens in a new tab)

Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.

The record behind the model

Why it is included

The provider-authored production paper identifies internal adapted speech models and combined systems and explicitly releases none of their weights, data or tooling. This record covers the specified proprietary adaptation/system; the original Qwen, Whisper and Canary base weights and stock-weight Turbo are not reclassified as closed.

Classification evidence (opens in a new tab)

Lifecycle dates

Paper submitted and public leaderboard listing described11 Sept 2026Source (opens in a new tab)

Sources reviewed