Grok 4.6 vs Gemini 3.1 Pro: Benchmarks, Price, Side-by-Side Tests (2026)

Comparison · August 2026

Grok 4.6 and Gemini 3.1 Pro are two frontier chat models people actually argue about in 2026. This guide is a decision piece, not a leaderboard dump: live pricing caveats, three workload cost scenarios, public benchmark signals, charts, and our own side-by-side runs on writing, coding, false premises, and product routing. Multi-model AI means you can keep both. Start in a multi-model AI workspace or on i10X.

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Persona picker

You are…	Start with	Why
Writer / CS / marketer	Grok 4.6 (often)	In our rewrite test, Grok stayed tighter to the facts; Gemini added warmer filler.
Developer / agent builder	Grok 4.6 default; Gemini for huge repos/docs	Public agentic indexes currently favor Grok 4.6; coding bug fix was a tie in our micro-test.
Researcher / analyst	Gemini 3.1 Pro	1M context + broader multimodal inputs (PDF/audio/video) for long packs.
Budget / high volume API	Grok 4.6	Same $2/M input, half the output price ($6 vs $12) at current API list rates.
Vision / screenshots / video	Gemini 3.1 Pro	Stronger public vision evals; native audio/video input on the API model card.

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What we are comparing (exact versions)

Multi-model AI means using more than one large language model in one work system. This page compares two specific API models, not vague “Grok vs Gemini” brand names and not multimodal-as-in-one-model marketing language.

Field	Grok 4.6	Gemini 3.1 Pro
Provider	xAI (listed as SpaceXAI in the API)	Google
API model	Grok 4.6	Gemini 3.1 Pro Preview
Listed API name	SpaceXAI: Grok 4.6	Google: Gemini 3.1 Pro Preview
Release (approx.)	12 Aug 2026 (press/AA coverage)	19 Feb 2026 (preview / later GA coverage)
App vs API note	Also available in xAI / X products; this article uses the API ID above	Also in Gemini app / Google AI Pro; this article uses the API preview ID above

If you still see posts comparing Grok 4 to Gemini 3 Pro without the 4.6 / 3.1 labels, treat them as older. For routing across many models, see AI model routing.

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Spec sheet (API pricing, 2026-08-21)

Spec	Grok 4.6	Gemini 3.1 Pro Preview
Context window	500,000 tokens	1,048,576 tokens
Input modalities (card)	text, image, file	text, image, file, audio, video
Output	text	text
Reasoning controls	reasoning / reasoning_effort supported	reasoning / reasoning_effort supported
Tools	tools / tool_choice	tools / tool_choice
Open weights	No	No
Vendor positioning (short)	Frontier coding, knowledge work, STEM	Frontier reasoning; software engineering; agentic reliability; multimodal foundation

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Pricing and real workload cost

List prices are easy to misread. Workload cost is what you feel. Rates below are from published API pricing on 2026-08-21.

Price	Grok 4.6	Gemini 3.1 Pro Preview
Input / 1M tokens	$2.00	$2.00
Output / 1M tokens	$6.00	$12.00
Cache read / 1M	$0.50	$0.20

Same input sticker. Gemini costs 2× on output. Gemini cache reads are cheaper if your stack actually hits cache.

Scenario	Assumed tokens	Est. Grok 4.6	Est. Gemini 3.1 Pro
Chat turn	1k in + 0.5k out	$0.005	$0.008
Repo / doc review	80k in + 4k out	$0.184	$0.208
Agent loop	200k in (50% cached) + 20k out	$0.370	$0.460

For subscription stacks (Plus / Pro / SuperGrok style plans), see AI subscription stack cost. Always verify live vendor pages before budgeting.

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Performance by job (public signals)

Public benches disagree by harness, effort mode, and date. Treat them as signals. Confirm with your prompts.

Signal	Grok 4.6	Gemini 3.1 Pro	Reading
Artificial Analysis Intelligence Index	~61 (high effort reporting)	~48 (index snapshots around Aug 2026)	Grok leads this composite in recent writeups
APEX-Agents	~57.5%	~33.5%	Grok stronger on long-horizon agent tasks in cited boards
GPQA Diamond	~93.2%	~94.3-94.4%	Near tie; Gemini often slight edge on science QA
Vision overall (Roboflow Vision Evals, Aug 2026)	~67.8%	~83.1%	Gemini clearer lead, especially object detection
Context	500K	~1M	Gemini for giant packs

Coding and agents

Recent Artificial Analysis coverage places Grok 4.6 on the intelligence frontier with strong agentic scores (APEX-Agents, GDPval-AA style boards). Gemini 3.1 Pro remains a serious engineering model with tool use, but the Aug 2026 public agentic gap in those writeups favors Grok. Throughput/speed measurements often favor Gemini’s token streaming even when agent indexes do not.

Writing and tone

Benchmarks barely measure voice. That is why we ran the email rewrite below. Expect Grok to sound more direct. Expect Gemini to sound more “polished corporate” and sometimes to add soft filler.

Multimodal and long context

This is Gemini’s clearest structural win: larger context and audio/video on the API model card, plus stronger public vision eval averages. If your day is PDFs, screenshots, and meeting video, Gemini is the safer default.

Job	Edge	Why
Hard / agentic work	Grok 4.6	Stronger recent agentic index signals
Everyday writing	Split (test tone)	Grok tighter to facts in our rewrite; Gemini warmer
Long docs / multimodal	Gemini 3.1 Pro	1M context + audio/video + vision lead
Realtime / X-native workflows	Grok family (product)	xAI/X product stack; confirm search tools in your app
Cost at output-heavy volume	Grok 4.6	$6 vs $12 output / 1M at current API list rates

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Side-by-side test (live API test, 2026-08-21)

We ran the same prompts on Grok 4.6 and Gemini 3.1 Pro Preview side by side in a multi-model workspace (temperature 0.2-0.3). Scores are editorial 1-5 across instruction following, depth, factual caution, style, and usefulness (max 25 per prompt).

Test 1: Client email rewrite

Task: Keep every fact. Warmer. Under 120 words.

Grok 4.6 (excerpt): Follow-up on the Q3 deck from last Tuesday; finance numbers still missing after the Friday promise; ask to move stakeholders to next week (Wednesday); update competitive slide with Acme pricing. Short, complete, no invented cheer.

Gemini 3.1 Pro (excerpt): Same facts, plus greeting energy (“hope you’re having a great week”), name placeholders, and softer closing. Warmer, slightly more corporate template.

Edge: Grok for fidelity and brevity. Gemini for polished warmth. If your brand voice hates filler, prefer Grok.

Test 2: Empty-list average bug

Both models correctly named ZeroDivisionError on empty input and proposed the same minimal guard (if not nums: return 0). Tie on this micro-task.

Test 3: False premise (Moon cheese)

Both refused the premise first. Grok was shorter. Gemini added a helpful redirect to real lunar resources. Both pass; Grok more concise, Gemini more pedagogical.

Test 4: Invented geography inflation

Grok refused Atlantis inflation and asked for a real statistical office. Gemini (earlier run) also refused and asked for a real country. Both pass the “do not invent numbers” bar. For trust workflows, still add a second-model check: multi-model hallucination checks.

Test 5: They disagree on the SaaS default (useful!)

Asked which model should be the SaaS team default for emails, long PDFs, Python, and screenshots:

• Grok’s matrix: Default Grok for email + Python; switch to Gemini for long PDFs and screenshots.
• Gemini’s matrix: Default Gemini for email, PDFs, screenshots; switch to Grok for heavy Python.

That disagreement is the point of multi-model stacks. The overlapping truth both matrices share: long PDFs and screenshots → Gemini; hard coding loop → often Grok. Email is taste.

Prompt	Grok 4.6	Gemini 3.1 Pro	Note
Email rewrite	23/25	21/25	Grok tighter to facts
Bug fix	24/25	24/25	Tie
False premise	24/25	23/25	Both refuse; Grok shorter
Refuse invented stat	24/25	24/25	Both refuse Atlantis rate
Routing matrix	23/25	22/25	Disagree on email default; agree on PDF/vision → Gemini
Total	118/125	114/125	Close; jobs still split

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Ecosystem and where you run them

• Grok 4.6: xAI API; consumer Grok experiences on xAI and X. Strength: realtime social graph in product contexts (confirm tools enabled).
• Gemini 3.1 Pro: Google AI / Gemini app / Workspace adjacency; API access. Strength: Docs/Drive/Search world and multimodal inputs.
• Both in one place: Multi-model workspaces like i10X let you compare the same prompt without two browser profiles.

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Pros, cons, and failure modes

Grok 4.6

• Pros: Strong recent agentic/intelligence index signals; cheaper output at matched $2 input; concise factual writing in our rewrite; good everyday coding loop.
• Cons: Smaller context than Gemini (500K vs ~1M); narrower modality set on the card (no audio/video listed); vision trails on public Roboflow averages.
• Fails when: you shove multi-hundred-page packs, video understanding, or screenshot-heavy QA into it as the only model.

Gemini 3.1 Pro

• Pros: 1M context; text+image+file+audio+video; stronger vision evals; Google ecosystem; competitive science QA.
• Cons: 2× output price vs Grok at current API list rates; can over-polish writing with filler; agentic boards in Aug 2026 writeups often trail Grok 4.6.
• Fails when: you optimize purely for output-token burn at scale, or you need the cheapest agent loop and ignore Gemini’s multimodal advantage.

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Decision guide: pick one or route both

If you need…	Choose
Output-cheap high volume text	Grok 4.6
Long PDF / video / screenshot pipelines	Gemini 3.1 Pro
Agentic multi-step knowledge work (per recent AA-style boards)	Start Grok 4.6; verify on your tools
Brand-safe warm customer email	A/B once; many teams will prefer Gemini polish or Grok brevity
Mixed SaaS week	Both: route PDF/vision → Gemini; code/agents/volume → Grok

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Application walkthroughs: where each model is better

1) Customer support email

Better often: Grok 4.6 when you want a short, faithful rewrite without invented niceties. In our live test, Grok preserved every operational fact and stayed under the word budget. Gemini produced a warmer letter but added greeting energy that was not in the source.

Switch to Gemini if your brand voice is deliberately polished and managers prefer “hope you are well” style scaffolding.

2) Long PDF / research pack

Better: Gemini 3.1 Pro. Structural advantages are hard to argue: ~1M context vs 500K, plus audio/video on the API modality list. If analysts paste 200-page decks, diligence PDFs, or mixed media, Gemini is the primary.

Use Grok for short/medium briefs, or as a second-pass critic after Gemini summarizes.

3) Everyday Python scripting

Often Grok 4.6 as the interactive coding partner, especially if you care about agentic boards from Aug 2026 coverage. Our micro bug-fix was a tie, so do not overclaim from one snippet. For multi-file refactors tied to huge docs or UI screenshots, bring Gemini in.

4) Screenshot and UI QA

Better: Gemini 3.1 Pro. Roboflow Vision Evals (mid-Aug 2026) show a clear overall gap (~83% vs ~68%), with object detection as the widest miss for Grok. If your loop is “screenshot → find the bug → draft a ticket,” default Gemini.

5) Output-heavy generation at API scale

Better on cost: Grok 4.6. Matched $2/M input, half the output rate ($6 vs $12). On our agent-loop estimate, Grok landed ~$0.37 vs Gemini ~$0.46 per stylized run. That compounds.

6) Graduate-level science QA

Near tie / slight Gemini on GPQA Diamond figures cited around 93-94%. Do not pick a stack from one science bench alone.

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Consumer plans vs API (do not mix them up)

SERP pages often blur ChatGPT-style subscriptions with API model IDs. Keep them separate:

• API comparison (this article): Grok 4.6 vs Gemini 3.1 Pro Preview in the API.
• Consumer apps: SuperGrok / X experiences vs Google AI Pro / Gemini app may expose different tool defaults, rate limits, and bundled models (including Flash tiers).

If your question is “which $20-class subscription feels better on my phone,” run a week-long lived test in both apps. If your question is “which model ID should my agent call,” use this API page.

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What changed since Grok 4 vs Gemini 3 Pro

Our earlier Grok 4 vs Gemini 3 Pro piece matched an older frontier pair. Grok 4.6 (Aug 2026) is the newer xAI flagship in this lane; Gemini 3.1 Pro is the Pro-class Google ID to compare against now. If you ranked for the old pair, keep that URL, update internal links here, and treat this page as the 2026-08 refresh.

Frequently asked questions

Which is better overall, Grok 4.6 or Gemini 3.1 Pro?
Neither permanently. Grok leads several Aug 2026 agentic/intelligence composites and wins on output price. Gemini wins context and multimodal breadth. Pick by job.

Which is better for coding?
Public agentic boards recently favor Grok 4.6. Our empty-list micro-test was a tie. For huge multimodal code+doc packs, Gemini’s context can matter more than the micro-test.

Which is better for writing?
Taste. In our rewrite, Grok stayed closer to the facts; Gemini sounded warmer and more templated. A/B on your brand voice.

Which is cheaper?
At published API rates (2026-08-21), input is $2/M for both; output is $6 (Grok) vs $12 (Gemini). Grok is cheaper on output-heavy work. Gemini cache reads are cheaper if you cache hard.

Which has the larger context window?
Gemini 3.1 Pro Preview (~1.05M) vs Grok 4.6 (500K) in the API.

Do I need both?
If your week mixes long documents, screenshots, and agentic coding, yes. That is the multi-model thesis.

Are we comparing apps or API models?
This page uses API models Grok 4.6 and Gemini 3.1 Pro Preview. Consumer apps may wrap different defaults or tools.

How often should I re-test?
After any major version bump (we just moved past Grok 4 / Gemini 3 Pro era). Monthly is sane for production teams.

Where can I run them side by side?
A multi-model workspace such as i10X workspace. Method guide: side-by-side AI comparison.

What about hallucinations and trust?
Both refused our false-premise and Atlantis traps. Still use source grounding and second-model checks for publishable claims. Multi-model hallucination checks.

Is Gemini 3.7 Flash a better comparison partner?
For speed/cost lanes, yes, compare Flash tiers separately. This page is Pro-class Gemini vs Grok flagship.

Did model choice ever change outcomes in i10X research?
Yes, in hiring evals: up to a 42 percentage-point hire-rate gap for the same candidate depending on which AI wrote the resume ( ai-cv-bias). Different domain, same moral: which model you call is a product decision.

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