Side-by-side pricing, features and compliance for any tools in the directory.
OpenAI
Pick it if: Sol replaces manual multi-agent orchestration for teams running the hardest coding and research workloads, not everyday chat. It's the default model inside the enterprise Copilot suite, so most business users already run it without choosing it directly, while cost-sensitive teams should route to a cheaper sibling model instead.
Its edge: State-of-the-art across coding, knowledge work, cybersecurity, and science benchmarks with 2x token efficiency vs competing flagships.
The catch: Premium pricing at $5/$30 per 1M tokens — 2.5x Terra, 5x Luna — limits high-volume use cases.
xAI
Pick it if: Grok 4.5 replaces Grok 4.3 as xAI's coding-focused model, fitting teams running high-volume agentic coding who want low cost per resolved task. It averages 15,954 output tokens per SWE-bench Pro task, well under Claude Opus 4.8's 67,020, at faster output speed than xAI's own prior release.
Its edge: Beats GPT-5.5 head-to-head on SWE-bench Pro (64.7% vs 58.6%), the one coding benchmark xAI chose to publish at launch.
The catch: No GPQA Diamond, AIME 2025, MMLU-Pro, or ARC-AGI 2 scores published at launch, so pure academic-reasoning performance is unverified.
| Input / 1M tokens | $5 | $2 |
|---|---|---|
| Output / 1M tokens | $30 | $6 |
| Cached input / 1M | $0.625 | $0.5 |
| Blended cost (3:1) | $11.25 | $3 |
| Free tier | false | false |
| Pricing model | per-token | per-token |
| Strengths | State-of-the-art across coding, knowledge work, cybersecurity, and science benchmarks with 2x token efficiency vs competing flagships.; Ultra multi-agent mode coordinates parallel subagents for faster complex task completion — unique at thi | Beats GPT-5.5 head-to-head on SWE-bench Pro (64.7% vs 58.6%), the one coding benchmark xAI chose to publish at launch.; Resolves the average coding-agent task in far fewer output tokens than Claude Opus 4.8, which compounds into lower real- |
|---|---|---|
| Limitations | Premium pricing at $5/$30 per 1M tokens — 2.5x Terra, 5x Luna — limits high-volume use cases.; Ultra mode and multi-agent beta features may have rough edges during early GA period.; No native audio/video I/O — vision only; multimodal laggin | No GPQA Diamond, AIME 2025, MMLU-Pro, or ARC-AGI 2 scores published at launch, so pure academic-reasoning performance is unverified.; Context window is the smallest of xAI's current model line-up, a real regression for teams with workflows |
| Context window | 200K | 500K |
|---|---|---|
| Max output tokens | 64K | — |
| Input modalities | text; image | text; image; tool-calls |
| Output modalities | text; tool-calls; code | text; tool-calls |
| Capabilities | Vision; Tool use; Code execution | Vision; Tool use; Web browsing |
| Reasoning modes | none; low; medium | low; medium; high |
| Long-context recall | high | unverified |
| Openness | proprietary | proprietary |
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