Side-by-side comparison of Gemini 3.6 Flash, Grok 4.5: pricing, capabilities, integrations and compliance — from verified HokAI records.
Google DeepMind
Pick it if: Gemini 3.6 Flash replaces the previous Flash generation as Google's cost-efficient workhorse for agentic coding and desktop automation, finishing tasks with 17% fewer output tokens along the way. Its knowledge cutoff advances a full 14 months to March 2026, making it the default pick for teams that outgrew the old Flash tier but don't need a full Pro-tier model.
Its edge: DeepSWE score jumped from 37% to 49% between Gemini 3.5 Flash and 3.6 Flash, the largest single-generation coding gain in the Flash line.
The catch: Architecture details, including dense vs mixture-of-experts and parameter count, are undisclosed.
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 | $1.50 | $2 |
|---|---|---|
| Output / 1M tokens | $7.50 | $6 |
| Cached input / 1M | $0.15 | $0.5 |
| Blended cost (3:1) | $3 | $3 |
| Free tier | false | false |
| Pricing model | per-token | per-token |
| Strengths | DeepSWE score jumped from 37% to 49% between Gemini 3.5 Flash and 3.6 Flash, the largest single-generation coding gain in the Flash line.; Supports parallel tool calls and configurable reasoning effort for multi-step agent orchestration.; S | 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 | Architecture details, including dense vs mixture-of-experts and parameter count, are undisclosed.; Priority-tier latency guarantees cost roughly 1.8x standard pricing.; MLE-Bench score of 63.9% still trails what frontier Pro-tier models rep | 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 | 1M | 500K |
|---|---|---|
| Max output tokens | 64K | — |
| Input modalities | text; image; video | text; image; tool-calls |
| Output modalities | text | text; tool-calls |
| Capabilities | Vision; Tool use; Audio input | Vision; Tool use; Web browsing |
| Reasoning modes | standard; configurable-thinking | low; medium; high |
| Long-context recall | high at 128K tokens, moderate at the full 1M window | unverified |
| Openness | proprietary | proprietary |
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