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Grok 4.5 vs MiniMax M3

Updated October 7, 2026. Rank says Grok 4.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Grok 4.5 has the higher public score estimate, 63.97 versus 54.39, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 8 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
xAI logo

xAI

63.97/100

Supported · Public rank #39

90% interval 59.2–68.8

Model B
MiniMax logo

MiniMax

54.39/100

Supported · Public rank #64

90% interval 45.6–63.2

Shared results
8
Grok 4.5 only
9
MiniMax M3 only
19
Like-for-like categories
3 / 8
Supported: Grok 4.5 and MiniMax M3How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Grok 4.5

    Grok 4.5 has the higher public coding point estimate, 57.7 to 37.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Grok 4.5

    Grok 4.5 has the higher public agentic point estimate, 57.6 to 39.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Long documents

    Prompts that approach the documented context limit

    MiniMax M3

    MiniMax M3 has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Repository review cost

    50K fresh input + 3K output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

57.7Grok 4.537.9MiniMax M3

Like-for-like · BenchAlign v5.8

Grok 4.5 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like
Grok 4.5
57.6
Supported · #29/122
MiniMax M3
39.7
Supported · #62/122
Basis
BenchAlign v5.8 lane · 4 vs 9 public rows
Reading
Grok 4.5 leads

Coding

Like-for-like
Grok 4.5
57.7
Supported · #27/146
MiniMax M3
37.9
Supported · #70/146
Basis
BenchAlign v5.8 lane · 8 vs 10 public rows
Reading
Grok 4.5 leads · intervals overlap

Knowledge

Like-for-like
Grok 4.5
67.0
Supported · #19/174
MiniMax M3
48.3
Supported · #77/174
Basis
BenchAlign v5.8 lane · 2 vs 2 public rows
Reading
Grok 4.5 leads · intervals overlap

Reasoning

Directional only
Grok 4.5
50.4
#28/28
MiniMax M3
79.4
#5/28
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Directional only

Multimodal

Not comparable
Grok 4.5
79.5
Unranked · 1 rankable row
MiniMax M3
51.5
#36/49
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Grok 4.5
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Grok 4.5
Not ranked
MiniMax M3
92.4
#5/125
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Grok 4.5
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Grok 4.5
$0.005
Fits in one request
MiniMax M3
$0.0009
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Grok 4.5
$0.118
Fits in one request
MiniMax M3
$0.0186
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Grok 4.5
$0.16
Fits in one request
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Grok 4.5

500K

MiniMax M3

1M

API model ID

Grok 4.5

Not sourced

MiniMax M3

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Grok 4.5

$0.3 per 1M cached input tokens

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

Grok 4.5

Not sourced

MiniMax M3

Not sourced

Documented outputs

Grok 4.5

Not sourced

MiniMax M3

Not sourced

Provider availability

Grok 4.5

Not sourced

MiniMax M3

Not sourced

Reasoning profile

Grok 4.5

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Grok 4.5

Proprietary

MiniMax M3

Open Weight

License

Grok 4.5

Proprietary

MiniMax M3

Open Weight

Release date

Grok 4.5

2026-07-08

MiniMax M3

2026-06-01

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Grok 4.5 has the higher public score estimate, 63.97 versus 54.39, but the 90% score intervals overlap.
Workload cost
Repository review: $0.118 vs $0.0186. Cache-heavy agent loop: $0.16 vs $0.03.
Context tradeoff
MiniMax M3 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Grok 4.5 or MiniMax M3?

Grok 4.5 has the higher public score estimate, 63.97 versus 54.39, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Grok 4.5 or MiniMax M3?

Grok 4.5 has the higher public coding point estimate, 57.7 to 37.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Grok 4.5 or MiniMax M3?

Grok 4.5 has the higher public agentic tasks point estimate, 57.6 to 39.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Grok 4.5 or MiniMax M3?

For the stated presets, chat costs $0.005 on Grok 4.5 and $0.0009 on MiniMax M3; repository review costs $0.118 and $0.0186; the cache-heavy agent loop costs $0.16 and $0.03. Costs use the listed standard API rates.

Which has the larger context window, Grok 4.5 or MiniMax M3?

MiniMax M3 has the larger documented context window: 1M, compared with 500K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence36 rows

Agentic

  • Terminal-Bench 3.0

    Grok 4.515.7%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.1

    Grok 4.583.3%
    Source
    MiniMax M366.0%
    Source

    Grok 4.5 leads this result

  • deepSwe

    Grok 4.553%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Grok 4.567.8%
    Source
    MiniMax M353.6%
    Source

    Grok 4.5 leads this result

  • BrowseComp

    Grok 4.5—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    Grok 4.5—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    Grok 4.5—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Grok 4.5—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Grok 4.5—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Grok 4.5—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Grok 4.5—
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    Grok 4.564.7%
    Source
    MiniMax M359%
    Source

    Grok 4.5 leads this result

  • SWE Multilingual

    Grok 4.578%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.1

    Grok 4.583.3%
    Source
    MiniMax M366.0%
    Source

    Grok 4.5 leads this result

  • CursorBench 3.2

    Grok 4.566.7%
    Source
    MiniMax M3—

    Not directly comparable

  • VulcanBench v3

    Grok 4.589.9%
    Source
    MiniMax M3—

    Not directly comparable

  • LiveCodeBench (Vals)

    Grok 4.587.4%
    Source
    MiniMax M382.2%
    Source

    Grok 4.5 leads this result

  • SWE-bench (Vals)

    Grok 4.586.6%
    Source
    MiniMax M375.0%
    Source

    Grok 4.5 leads this result

  • PostTrainBench v1.1

    Grok 4.523.4%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Verified

    Grok 4.5—
    MiniMax M380.5%
    Source

    Not directly comparable

  • NL2Repo

    Grok 4.5—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Grok 4.5—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Grok 4.5—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Grok 4.5—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Grok 4.5—
    MiniMax M348.4%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Grok 4.552.6%
    Source
    MiniMax M3—

    Not directly comparable

  • ARC-AGI-3

    Grok 4.50.3%
    Source
    MiniMax M3—

    Not directly comparable

  • ARC-AGI-1

    Grok 4.585.67%
    Source
    MiniMax M3—

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Grok 4.5—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Grok 4.5—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Grok 4.5—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Grok 4.5—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Grok 4.5—
    MiniMax M385.4%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Grok 4.592.9%
    Source
    MiniMax M392.7%
    Source

    Grok 4.5 leads this result

  • MMLU-Pro (Vals)

    Grok 4.589.2%
    Source
    MiniMax M384.2%
    Source

    Grok 4.5 leads this result

Math

  • USAMO 2026

    Grok 4.5—
    MiniMax M385.7%
    Source

    Not directly comparable

36 public results · 8 shared

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Last updated October 7, 2026