Grok 4.6
xAIKey grok-4.6Also reported as xai/grok-4.6, combo/grok-4.6, grok/grok-4.6, cursor/grok-4.6, x-ai/grok-4.6, grok-sub/grok-4.6, grok2api/grok-4.6, [次]grok-4.6, hr-gr/grok-4.6, grok-oauth/grok-4.6, shuo/grok-4.6, xai-oauth/grok-4.6, gcli/grok-4.6
- Rank
- #44
- by active users
- Active users
- 41
- Down 114 from 155 active users in the previous 30 days. vs previous 30 days
- Adoption
- 4.3%
- of 956 accounts
- Tokens
- 4B
- cache included
- Est. cost
- $1.5K
- at public list prices
- First seen
- May 21, 2026
- in any submission
Oct 15 – Nov 13, 2026 (UTC)956 accounts100% of tokens from an identified modelData through Nov 13, 2026, 01:06 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
0 active users on Nov 13, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Oct 15, 2026 | 12 | 594.8M |
| Oct 16, 2026 | 10 | 221.5M |
| Oct 17, 2026 | 10 | 336.3M |
| Oct 18, 2026 | 14 | 141.6M |
| Oct 19, 2026 | 9 | 91.6M |
| Oct 20, 2026 | 7 | 19.4M |
| Oct 21, 2026 | 8 | 152M |
| Oct 22, 2026 | 10 | 233.1M |
| Oct 23, 2026 | 12 | 177.6M |
| Oct 24, 2026 | 9 | 279.4M |
| Oct 25, 2026 | 8 | 219.9M |
| Oct 26, 2026 | 9 | 158.5M |
| Oct 27, 2026 | 10 | 74.2M |
| Oct 28, 2026 | 7 | 149.7M |
| Oct 29, 2026 | 7 | 37.2M |
| Oct 30, 2026 | 10 | 133.5M |
| Oct 31, 2026 | 6 | 107.8M |
| Nov 1, 2026 | 5 | 135.5M |
| Nov 2, 2026 | 3 | 77.3M |
| Nov 3, 2026 | 8 | 50.3M |
| Nov 4, 2026 | 4 | 133.9M |
| Nov 5, 2026 | 8 | 93.1M |
| Nov 6, 2026 | 6 | 48.7M |
| Nov 7, 2026 | 4 | 22.8M |
| Nov 8, 2026 | 6 | 103.2M |
| Nov 9, 2026 | 6 | 84.1M |
| Nov 10, 2026 | 3 | 92.2M |
| Nov 11, 2026 | 1 | 5M |
| Nov 12, 2026 | 2 | 4.3M |
| Nov 13, 2026 | 0 | 0 |
Token mix
How the 4B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input10%
- Output0.4%
- Cache read89%
- Cache write0%
- Reasoning0.6%
Agents that carry Grok 4.6
Each agent's share of this model's tokens, and how many accounts used the model through it.
Grok Build51% of this model's tokens27active users
Hermes Agent26% of this model's tokens5active users
Aside12% of this model's tokens4active users
Senpi (OmO Native)7.6% of this model's tokens4active users
ZCode2.1% of this model's tokens1active users
Pi0.6% of this model's tokens1active users
OpenClaw0.3% of this model's tokens1active users
OpenCode0.2% of this model's tokens2active users
Claude Code0.1% of this model's tokens2active users
Oh My Pi<0.1% of this model's tokens3active users
Benchmarks
The best result for Grok 4.6 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.
- Epoch Capabilities IndexOverall · Epoch AI157.8
Epoch Capabilities Index: 157.8
- Model
- Grok 4.6
- Listed as
- Grok 4.6
- Conditions
- Not reported
- Interval
- 155.8–159.9
- Unit
- ECI
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #28 of 158 matched modelsNo conditions reportedModel released Aug 12, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench19.7%
Terminal-Bench 4.1: 19.7%
- Model
- Grok 4.6
- Listed as
- Grok 4.6
- Conditions
- High · Grok Build
- Interval
- 16.6–22.8%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Rank #16 of 23 matched modelsHigh · Grok BuildPublished Nov 3, 2026Source: tbench.ai (opens in a new tab)
Tokscale usage: Grok Build carried 51% of Grok 4.6 tokens in the last 30 days (27 active users). - CursorBenchAgentic coding · Cursor, collected by Epoch AI41.4%
CursorBench: 41.4%
- Model
- Grok 4.6
- Listed as
- Grok 4.6 Extra High
- Conditions
- XHigh
- Unit
- score
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Best of 4 reported results for this model.
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #15 of 21 matched modelsXHighModel released Aug 12, 2026Source: cursor.com (opens in a new tab)Show 3 more results with other run conditionsHide the other results
- Listed as Grok 4.6 High40.4%
CursorBench: 40.4%
- Model
- Grok 4.6
- Listed as
- Grok 4.6 High
- Conditions
- High
- Unit
- score
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Grok 4.6 Medium36.1%
CursorBench: 36.1%
- Model
- Grok 4.6
- Listed as
- Grok 4.6 Medium
- Conditions
- Medium
- Unit
- score
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Grok 4.6 Low33.4%
CursorBench: 33.4%
- Model
- Grok 4.6
- Listed as
- Grok 4.6 Low
- Conditions
- Low
- Unit
- score
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- DeepSWEAgentic coding · Datacurve, collected by Epoch AI67.5%
DeepSWE: 67.5%
- Model
- Grok 4.6
- Listed as
- grok-4-6 (medium)
- Conditions
- Medium · mini-swe-agent
- Interval
- 65.2–69.8%
- Unit
- pass@1
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Best of 4 reported results for this model.
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #9 of 26 matched modelsMedium · mini-swe-agentModel released Aug 12, 2026Source: deepswe.datacurve.ai (opens in a new tab)Show 3 more results with other run conditionsHide the other results
- Listed as grok-4-6 (xhigh)66.7%
DeepSWE: 66.7%
- Model
- Grok 4.6
- Listed as
- grok-4-6 (xhigh)
- Conditions
- XHigh · mini-swe-agent
- Interval
- 64.6–68.9%
- Unit
- pass@1
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as grok-4-6 (high)65.2%
DeepSWE: 65.2%
- Model
- Grok 4.6
- Listed as
- grok-4-6 (high)
- Conditions
- High · mini-swe-agent
- Interval
- 63.7–66.7%
- Unit
- pass@1
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as grok-4-6 (low)41.6%
DeepSWE: 41.6%
- Model
- Grok 4.6
- Listed as
- grok-4-6 (low)
- Conditions
- Low · mini-swe-agent
- Interval
- 39.3–44.0%
- Unit
- pass@1
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI25.3%
FrontierSWE: 25.3%
- Model
- Grok 4.6
- Listed as
- Grok 4.6
- Conditions
- XHigh · proximus
- Unit
- mean@5
- Model released
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #16 of 23 matched modelsXHigh · proximusModel released Aug 12, 2026Source: frontierswe.com (opens in a new tab) - WebDev ArenaWeb development · LMArena1,617
WebDev Arena: 1,617
- Model
- Grok 4.6
- Listed as
- Grok 4.6 (High)
- Conditions
- High
- Interval
- 1609–1624
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- Agent ArenaAgents · LMArena+0.01
Agent Arena: +0.01
- Model
- Grok 4.6
- Listed as
- Grok 4.6 (xHigh)
- Conditions
- XHigh · Arena Agent Mode
- Interval
- -0.00 to 0.02
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #28 of 48 matched modelsXHigh · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI94.0%
GPQA Diamond: 94.0%
- Model
- Grok 4.6
- Listed as
- grok-4.6_high
- Conditions
- High
- Unit
- % correct
- Run date
- Aug 12, 2026
- Retrieved
- Nov 12, 2026
Best of 2 reported results for this model.
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.
Show 1 more result with other run conditionsHide the other results
- Listed as grok-4.6_xhigh93.2%
GPQA Diamond: 93.2%
- Model
- Grok 4.6
- Listed as
- grok-4.6_xhigh
- Conditions
- XHigh
- Unit
- % correct
- Run date
- Aug 14, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI66.0%
FrontierMath Tiers 1–3 (v2): 66.0%
- Model
- Grok 4.6
- Listed as
- grok-4.6_xhigh
- Conditions
- XHigh
- Unit
- % solved
- Run date
- Aug 14, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.
- SimpleQA VerifiedKnowledge · Epoch AI49.3%
SimpleQA Verified: 49.3%
- Model
- Grok 4.6
- Listed as
- grok-4.6_high
- Conditions
- High
- Unit
- % correct
- Run date
- Aug 27, 2026
- Retrieved
- Nov 12, 2026
Best of 2 reported results for this model.
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Show 1 more result with other run conditionsHide the other results
- Listed as grok-4.6_xhigh48.9%
SimpleQA Verified: 48.9%
- Model
- Grok 4.6
- Listed as
- grok-4.6_xhigh
- Conditions
- XHigh
- Unit
- % correct
- Run date
- Aug 27, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. xAI is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $0.71
- Est. per 1M tokens
89% cache reads - At the community mix
- $0.57
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $3
- Per 1M tokens at list prices
No cache
Cache reads were 89% of Grok 4.6 tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- xAI list prices per 1M tokens: input $2, output $6, cache read $0.50.
- This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
- The community mix is the tokens of every identified model in the last 30 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
- No cache-write price is listed, so cache writes are priced as input.
List prices by provider
- xAIReference
grok-4.6$2 input per 1M tokens$6 output per 1M tokens$0.50 cache read per 1M tokensCache write not listed500K tokens of context - Amazon Bedrock
xai.grok-4.6$2.20 input per 1M tokens$6.60 output per 1M tokens$0.55 cache read per 1M tokensCache write not listed500K tokens of context - Vertex
xai/grok-4.6$2 input per 1M tokens$6 output per 1M tokens$0.50 cache read per 1M tokensCache write not listed524K tokens of context - Azure
grok-4.6$2 input per 1M tokens$6 output per 1M tokens$0.50 cache read per 1M tokensCache write not listed200K tokens of context
Show 2 more providersShow fewer providers
- OpenRouter
x-ai/grok-4.6$2 input per 1M tokens$6 output per 1M tokens$0.50 cache read per 1M tokensCache write not listed500K tokens of context - Vercel AI Gateway
spacexai/grok-4.6$2 input per 1M tokens$6 output per 1M tokens$0.50 cache read per 1M tokensCache write not listed500K tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 500K tokens
- Max output
- 500K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- Feb 1, 2026
- Release date
- Aug 12, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used Grok 4.6 most in this period, by tokens. Hidden accounts are never listed.
- 1
Mark Ferraz@mferraznw1.3Btokens$293est. cost18active days$293 est. cost · 18 active days
- 2
Soju06@Soju06944.6Mtokens—est. cost27active daysno price · 27 active days
- 3
Sangrak Choi@kargnas407Mtokens$295est. cost17active days$295 est. cost · 17 active days
- 4
siddicky@siddicky347.7Mtokens$217est. cost13active days$217 est. cost · 13 active days
- 5
Code_G@codeg-dev290.3Mtokens$96est. cost10active days$96 est. cost · 10 active days
- 6
Sunghyun Cho@anaclumos178.4Mtokens$152est. cost4active days$152 est. cost · 4 active days
- 7
WONJUN SEO@ownuun163Mtokens$135est. cost5active days$135 est. cost · 5 active days
- 8
Zhen Huang@ZhenHuangLab138.7Mtokens$95est. cost28active days$95 est. cost · 28 active days
- 9
Alireza Bashiri@al3rez105Mtokens$108est. cost6active days$108 est. cost · 6 active days
- 10
Minseo Choi@trac3r0019.9Mtokens$14est. cost4active days$14 est. cost · 4 active days
More from xAI
Other xAI models in the same period, by active users.
- Grok 4.713% adoption128active users
- Grok Bot Default2.7% adoption26active users
- Grok 4.7 Build Fast2.6% adoption25active users
- Grok Bot Automation1.9% adoption18active users
- Grok 4.7 High Fast1.5% adoption14active users
- Grok 4.7 High1.5% adoption14active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.