Model comparison

Kimi K3.1 Pro vs Grok 4.6

Moonshot AI's Kimi K3.1 Pro against xAI's Grok 4.6: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.

CheaperGrok 4.6

Grok 4.6 lists at $3.00 per million tokens blended against $4.00 for Kimi K3.1 Pro - 1.3x less.

Stronger on intelligenceKimi K3.1 Pro

Kimi K3.1 Pro scores 46 on the intelligence index against 44 - 2 points apart.

Longer contextKimi K3.1 Pro

Kimi K3.1 Pro reads 1.0M tokens at once, Grok 4.6 500k.

NewerKimi K3.1 Pro

Kimi K3.1 Pro was released about 2 months later.

Side by side

Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).

Specification	Kimi K3.1 Pro	Grok 4.6
Input price / 1M tokens	$2.00	$2.00
Output price / 1M tokens	$10.0	$6.00
Blended (3 in : 1 out)	$4.00	$3.00
Cached input / 1M	$0.20	$0.50
Context window	1.0M	500K
Max output	944K	450K
Input	text, image, video	text, image, file
Output	text	text
Tool calls
Structured output
Reasoning
Open weights
Intelligence index	46	44
Coding index	-	77
Agentic index	-	53
Released	Oct 23, 2026	Aug 12, 2026
Available on this deployment

What a month costs

List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.

Workload	Kimi K3.1 Pro	Grok 4.6	Difference
Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.	$90.00	$70.00	$20.00 less on Grok 4.6
Document summaries100M in, 5M out - long inputs, short answers.	$250	$230	$20.00 less on Grok 4.6
Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.	$320	$240	$80.00 less on Grok 4.6

What the router does with the pair

Grok 4.6 takes the short and general requests - at $3.00 blended it is the default - and Kimi K3.1 Pro the ones whose complexity or quality floor rules the cheaper model out. The split is per request, not per app, and every decision carries the scores for both.

Price a request Playground

yaml

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
  - { id: grok-4.6, kind: llm, metadata: { model: x-ai/grok-4.6 } }
  - { id: kimi-k3.1-pro, kind: llm, metadata: { model: moonshotai/kimi-k3.1-pro } }

# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
  - name: simple-requests-stay-cheap
    when: { max_complexity: 0.45 }
    prefer: [grok-4.6]
    weight: 0.8
  - name: hard-requests-escalate
    when: { min_complexity: 0.45 }
    prefer: [kimi-k3.1-pro]
    weight: 0.8

Frequently asked

Is Kimi K3.1 Pro cheaper than Grok 4.6?: No. Kimi K3.1 Pro lists at $2.00 in / $10.0 out per million tokens, Grok 4.6 at $2.00 in / $6.00 out; blended, Grok 4.6 is the cheaper one.
Which is better, Kimi K3.1 Pro or Grok 4.6?: On the Artificial Analysis intelligence index Kimi K3.1 Pro scores higher (46 against 44). "Better" depends on the task: the coding and agentic indexes below and the abilities row may point the other way for your requests.
Which has the longer context window?: Kimi K3.1 Pro - 1.0M tokens against 500K.
Can I use Kimi K3.1 Pro and Grok 4.6 together?: Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

Also compared

Every Moonshot AI and xAI model, with prices, is on the vendor pages; the rankings show what the router actually picks.

For the business

What it means for which models you pay for.

Catalogue of every vendor
The right model, not the famous one
Price, context, abilities and benchmark indexes side by side, with the model that fits each task named.
The rankings
89% less
Lower cost per request
On the 150-prompt benchmark the router spent 89% less than sending every prompt to the reference model, and the judged quality went up, not down.
Read the benchmark
Per million tokens, every model
Prices you can compare
The catalogue prints input and output prices and what three typical monthly workloads cost on each.
The model catalogue

Which LLM is the cheapest for our workload?: The best-for pages rank the live catalogue per task by the index that measures it, and the router picks the cheapest model that meets your quality rule for each request.
How much can we save on our LLM bill?: On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.
How often do model prices change?: The catalogue is refreshed from the vendors' price lists; each model page shows the date of its data.

Stop choosing between Kimi K3.1 Pro and Grok 4.6. Route to both.

Declare the pair as targets and OpenSmartRoute picks per request - the cheaper one where it holds up, the stronger one where it matters - with the comparison in every trace.

Create a free account Try a request

Free plan, no card. Fifteen thousand decisions a month with the full trace.

Specification

Kimi K3.1 Pro

Grok 4.6

Input price / 1M tokens

$2.00

Output price / 1M tokens

$10.0

$6.00

Blended (3 in : 1 out)

$4.00

$3.00

Cached input / 1M

$0.20

$0.50

Context window

1.0M

500K

Max output

944K

450K

Input

text, image, video

text, image, file

Output

text

Tool calls

Structured output

Reasoning

Open weights

Intelligence index

Coding index

Agentic index

Released

Oct 23, 2026

Aug 12, 2026

Available on this deployment

Workload

Kimi K3.1 Pro

Grok 4.6

Difference

Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.

$90.00

$70.00

$20.00 less on Grok 4.6

Document summaries100M in, 5M out - long inputs, short answers.

$250

$230

$20.00 less on Grok 4.6

Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.

$320

$240

$80.00 less on Grok 4.6

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry) targets: - { id: grok-4.6, kind: llm, metadata: { model: x-ai/grok-4.6 } } - { id: kimi-k3.1-pro, kind: llm, metadata: { model: moonshotai/kimi-k3.1-pro } } # rules.yaml - the cheaper model by default, the stronger one when the request is hard rules: - name: simple-requests-stay-cheap when: { max_complexity: 0.45 } prefer: [grok-4.6] weight: 0.8 - name: hard-requests-escalate when: { min_complexity: 0.45 } prefer: [kimi-k3.1-pro] weight: 0.8

Frequently asked

Is Kimi K3.1 Pro cheaper than Grok 4.6?

No. Kimi K3.1 Pro lists at $2.00 in / $10.0 out per million tokens, Grok 4.6 at $2.00 in / $6.00 out; blended, Grok 4.6 is the cheaper one.

Which is better, Kimi K3.1 Pro or Grok 4.6?

On the Artificial Analysis intelligence index Kimi K3.1 Pro scores higher (46 against 44). "Better" depends on the task: the coding and agentic indexes below and the abilities row may point the other way for your requests.

Which has the longer context window?

Kimi K3.1 Pro - 1.0M tokens against 500K.

Can I use Kimi K3.1 Pro and Grok 4.6 together?

Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

Kimi K3.1 Pro vs Grok 4.6

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between Kimi K3.1 Pro and Grok 4.6. Route to both.

Kimi K3.1 Pro vs Grok 4.6

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between Kimi K3.1 Pro and Grok 4.6. Route to both.