AP
Apodex 1.1
Apodex · Proprietary · rank 109 · bench-align-v5
Canonical idapodex-1-1
Access typeProprietary
Blended $/1MUnavailable75% input / 25% output
Capability shape
Seven axes from the ranking source. A missing axis is drawn as a gap.
Runtime service evidence
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: ObservedUnavailable
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | Unavailable | Unavailable | Unavailable | |
| Throughput | Unavailable | Unavailable | Unavailable |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Endpoint and price matrix
Every published price component, including cache reads and writes.
Self-hosted listingApodex's web workbench uses dynamic credit billing based on model tokens and tool calls, while the release post says bare-model API access will roll out later. Apodex does not publish a comparable first-party input/output token rate or context limit for the full 397B model.No hosted token rate was published for this model, so its per-token price is unavailable rather than zero.
Workload-aware monthly cost example
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
Modelled monthly costUnavailableThe applicable input rate is unavailable.
Modelled tokensUnavailable
Open the simulatorChange this workload
Benchmark record
24 matched benchmark rows with their published value, unit, and provenance.
Knowledge
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| BioMysteryBench (human-difficult) BioMysteryBench Human Difficult | 35.3 | Human-difficult computational biology investigations | Frontier computational biology | Claude Opus 5 System Card |
| HLE Humanity's Last Exam | 56.1 | Expert-level questions | Frontier expert level | Humanity's Last Exam |
| Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index | 30.4 | Cross-benchmark intelligence index | Display-only external reference | Artificial Analysis |
| AA-GPQA Diamond Artificial Analysis GPQA Diamond | 86.4 | Graduate-level science questions | Graduate-level science reasoning | Artificial Analysis GPQA Diamond Benchmark Leaderboard |
| AA-HLE Artificial Analysis Humanity's Last Exam | 34.1 | Expert-level questions | Frontier expert reasoning | Artificial Analysis Humanity's Last Exam Benchmark Leaderboard |
| AA-Omniscience Index Artificial Analysis Omniscience Index | -21.9 | Knowledge questions | Broad factual knowledge | AA-Omniscience: Knowledge and Hallucination Benchmark |
| AA-Omniscience Accuracy Artificial Analysis Omniscience Accuracy | 31.7 | Knowledge questions | Broad knowledge | Artificial Analysis model benchmarks |
| AA-Omniscience Hallucination Rate Artificial Analysis Omniscience Hallucination Rate | 78.4 | Knowledge questions | Factuality | Artificial Analysis model benchmarks |
| FrontierScience Research FrontierScience Research | 63.3 | Scientific research problems | Frontier scientific research | Muse Spark Eval Methodology |
Coding
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 70.8 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| SWE-bench Verified Software Engineering Benchmark Verified | 77.7 | 500 verified issues | Professional software engineering | SWE-bench: Can Language Models Resolve Real-World GitHub Issues? |
| AA Coding Index Artificial Analysis Coding Index | 60.8 | Cross-benchmark coding index | Display-only external reference | Artificial Analysis model leaderboards |
| AA-SciCode Artificial Analysis SciCode | 45.5 | Scientific coding subproblems | Scientific programming | Artificial Analysis SciCode Benchmark Leaderboard |
Mathematics
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| IMO 2026 International Mathematical Olympiad 2026 | 31 | 6 proof-based problems | International olympiad mathematics | Claude Opus 5 System Card |
Reasoning
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-LCR Artificial Analysis Long Context Reasoning | 79.3 | Long-context reasoning tasks | Long-context reasoning | Artificial Analysis model benchmarks |
| CritPt Critical Physics Tasks | 4.6 | Research-level physics questions | Research-level physics reasoning | CritPt Benchmark Leaderboard |
Agentic
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 70.8 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| HLE w/ tools Humanity's Last Exam with tools | 56.1 | Expert questions with tool use | Frontier tool-augmented reasoning | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA | 1273 | Agentic real-world work tasks | Professional agentic workflows | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA normalized | 38.7 | Economically valuable tasks | Professional agentic workflows | Artificial Analysis model benchmarks |
| APEX-Agents-AA APEX-Agents-AA | 31.2 | 452 professional-services agent tasks | Long-horizon workplace agent tasks | APEX-Agents-AA Benchmark Leaderboard |
| APEX-Agents APEX-Agents | 38.5 | Professional-services agent tasks | Long-horizon professional work | Kimi K3: Open Frontier Intelligence |
| DeepSearchQA DeepSearchQA | 92.4 | Agentic browsing and list-answer questions | Agentic web research | Muse Spark Eval Methodology |
Multimodal & Grounded
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-MMMU-Pro Artificial Analysis MMMU-Pro | 79.2 | Multimodal academic reasoning | Frontier multimodal | Artificial Analysis MMMU-Pro Benchmark Leaderboard |
Lifecycle and limitations log
Lifecycle events the source associates with this model, plus what this profile does not claim.
No lifecycle event references this model.
That is not evidence the model has no lifecycle plan — only that this source published none.
What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-09-17 17:17 UTC.