Grok 4.6 is xAI's best model for research — it scores 88/100 vs 86/100 for Grok 4, at $2/1M input tokens. Across all providers, GPT-6 Astra still leads research at 100/100 — worth considering if you're not committed to xAI.
The safest xai model for research default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Grok 4.6 is the strongest answer here for xai model for research — pick it when quality of output matters more than the $2.00/1M/1M input you pay for it.
GPT-5.1-Codex-Max is the cheaper way in for xai model for research, at $1.25/1M/1M input against Grok 4.6's $2.00/1M/1M.
Grok 4 carries 2M tokens of context, so it is the pick for xai model for research when whole documents, transcripts, or repositories go in at once.
Grok 4.6 leads xAI's lineup for research at 88/100 ($2/1M input, 500K context).
Grok 4.6 is the value pick at $2/1M input with a research score of 88/100.
GPT-6 Astra (OpenAI) is the overall research leader at 100/100 if provider choice is open.
Choose Grok 4.6 when research quality is the priority and you're staying on xAI.
Choose Grok 4.6 when token volume matters more than peak quality.
Teams open to other providers should also evaluate GPT-6 Astra before committing.
Switch the scoring lens to see whether the xai model for research answer changes when cost, speed, or long-document depth leads the decision.
xAI / Balanced / Aug 27, 2026
Finishes agent tasks in half the turns — cheap where it counts.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need a published SWE-bench score to justify the pick, or your prompts routinely cross 200K tokens where the price doubles.
Where the xai model for research recommendation shifts once you weigh price or latency differently.
Finishes agent tasks in half the turns — cheap where it counts.
Strong coding value with 2M context — an underrated pick at this price.
Best cost-per-solved-task coding agent — efficiency over ceiling.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Grok 4.6xAI | $2.00/1M | $6.00/1M | $32 | 500k tokens | Fast | 86 | 84 | 88 |
| Grok 4xAI | $2.00/1M | $6.00/1M | $32 | 2M tokens | Fast | 92 | 70 | 86 |
| Grok 4.5xAI | $2.00/1M | $6.00/1M | $32 | 500k tokens | Fast | 94 | 72 | 84 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for xai model for research, what it is genuinely good at, and where we would steer you away from it.
The default answer for xai model for research — 86/100 on the coding axis, and the model we would start with unless the price below rules it out.
xAI's long-horizon agent model — it finishes agentic tasks in roughly half the turns of its rivals, which makes it cheaper in practice than its per-token price suggests.
You need a published SWE-bench score to justify the pick, or your prompts routinely cross 200K tokens where the price doubles.
Buy it for turn efficiency, not for benchmark ceilings. On long agent runs, finishing in half the turns beats a model that scores two points higher and takes twice as many round trips.
Full pricing, benchmark table and release notes on the Grok 4.6 page.
In this line-up because of context depth: the pick for xai model for research when the input is too big to chunk.
xAI's latest flagship with strong coding benchmark performance, a 2M token context window, and aggressive pricing at $2/$6 per million tokens.
You need the highest writing quality or the most reliable production-grade output — Claude wins both.
Strong coding benchmark with excellent value. The $2/$6 pricing and 2M context make it competitive with more expensive alternatives.
Full pricing, benchmark table and release notes on the Grok 4 page.
Rounds out the shortlist for xai model for research at 94/100 on coding.
Best cost-per-solved-task coding agent — efficiency over ceiling. Full Grok 4.5 review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Grok 4.6 — it scores 88/100 on research in this directory, ahead of Grok 4 at 86/100. Finishes agent tasks in half the turns — cheap where it counts.
Not overall. GPT-6 Astra (OpenAI) leads the directory for research at 100/100 vs Grok 4.6's 88/100. Grok 4.6 is the best pick if you're staying within xAI's ecosystem.
Grok 4.6 at $2/1M input tokens (research score: 88/100). Use it for volume work and reserve Grok 4.6 for the tasks where quality matters most.
$2/1M input tokens and $6/1M output tokens via the API, or through SuperGrok at $30/mo for chat use. Context window: 500K tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $32.00, against $32.00 for Grok 4.6.
No published SWE-bench Verified or SWE-bench Pro figure, so it cannot be compared directly on the standard coding leaderboard. GPT-5.6 Sol Max beats it on DeepSWE v1.1 and Terminal-Bench 3.0. Concretely, avoid it if you need a published SWE-bench score to justify the pick, or your prompts routinely cross 200K tokens where the price doubles. If none of that is negotiable, GPT-6 Astra (OpenAI) is the cross-provider leader at 100/100.
long-horizon research agents that work a topic across many sequential steps, working through an unfamiliar codebase over an extended agent session, and interactive and visual work where turn count drives the real bill. Its 500K-token context window is the practical limit on how much you can hand it in one go.
They are the same model here — Grok 4.6 is both xAI's strongest research pick and its best value, so there is no trade-off to make.