Data as of October 29, 2026 · How the score is built
Phonic-1
Decision readingPhonic-1 is tracked, but not publicly ranked yet. Published speech or voice results from Phonic-1 launch evaluation appear below. They do not produce a weighted text-model score.
Released Oct 29, 2026 — see all recent releases
Voice benchmark evidence
Phonic-1 launch evaluation is an owner-defined voice evaluation. Its result stays separate from BenchLM's weighted text-model ranking.
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedPhonic model documentation
- Context window
- N/A
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Available since October 29, 2026 through Phonic’s hosted agent platform and API, with 51 documented agent languages. Phonic has not published a public model ID; Cekura’s benchmark setup calls it `phonic_v1` at the “Intelligence high” setting. No weights are published.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordPhonic model documentation
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track Phonic-1, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.
Phonic-1 is a proprietary model with a N/A context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available since October 29, 2026 through Phonic’s hosted agent platform and API, with 51 documented agent languages. Phonic has not published a public model ID; Cekura’s benchmark setup calls it `phonic_v1` at the “Intelligence high” setting. No weights are published.
Phonic-1 is Phonic’s hosted speech-to-speech model for voice agents that call tools. It is trained on more than 50 languages, can switch language mid-call with the same voice, and has a configurable intelligence setting; Phonic reports results at the high setting. Its voice evaluations stay separate from weighted text-model scores.
Speech or voice evidence appears above; text-model benchmark coverage remains empty.
Last updated October 29, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Phonic-1 perform overall in AI benchmarks?
Phonic-1 has published speech or voice results in Phonic-1 launch evaluation. Those results remain separate from the weighted text-model ranking, so this profile does not assign a BenchLM score or overall rank. Use the linked evaluation's metric and run conditions to compare speech systems.
Does Phonic-1 have full benchmark coverage on BenchLM?
No. Phonic-1's speech or voice results appear in Phonic-1 launch evaluation, but it has no published text-model benchmark rows. The voice evaluation does not fill the text-model coverage slots or produce an overall rank. Missing text coverage is not treated as a zero score.
What is the context window size of Phonic-1?
Phonic-1 has a reported context window of N/A in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.