Skip to main content
Radar

Keep up with the models you depend on. Follow price changes, retirements, and API updates.Follow the models you depend on.

Follow model changes
BenchLM
Meta logo
Model A
Llama 4 Maverick

Meta

22.11/100

Supported · Public rank #237

90% interval 16.8–27.4

Llama 4 Maverick vs Mercury Edit 2

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Inception logo
Model B
Mercury Edit 2

Inception

—

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Share or export

Share on XLinkedInSocial cardCSVJSON

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.

  • Long documents

    Prompts that approach the documented context limit

    Llama 4 Maverick

    Llama 4 Maverick has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Mercury Edit 2 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Mercury Edit 2 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Mercury Edit 2 does not fit this workload in one request. Llama 4 Maverick has no comparable published API token rate.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

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

Shared results
0
Llama 4 Maverick only
1
Mercury Edit 2 only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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

Not comparable
Llama 4 Maverick
23.8
Estimated · #148/152
Mercury Edit 2
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Llama 4 Maverick
25.1
Estimated · #147/151
Mercury Edit 2
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Llama 4 Maverick
55.4
Unranked · 2 rankable rows
Mercury Edit 2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Llama 4 Maverick
30.5
Estimated · #175/183
Mercury Edit 2
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Llama 4 Maverick
25.3
Unranked · 1 rankable row
Mercury Edit 2
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Llama 4 Maverick
Not ranked
Mercury Edit 2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Llama 4 Maverick
51.5
Unranked · 1 rankable row
Mercury Edit 2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Llama 4 Maverick
50.5
#81/123
Mercury Edit 2
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

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

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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

Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
Mercury Edit 2
$0.00063
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
Mercury Edit 2
$0.01475
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Cache-heavy agent loop

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

Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Mercury Edit 2
$0.0175
Does not fit in one request

Mercury Edit 2 does not fit this workload in one request. Llama 4 Maverick has no comparable published API token rate.

Specification differences

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

Cached-input rate

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

Llama 4 Maverick

No comparable hosted API rate

Mercury Edit 2

$0.025 per 1M cached input tokens

Inception Mercury Edit 2 launch post

Documented inputs

Llama 4 Maverick

Not sourced

Mercury Edit 2

Not sourced

Documented outputs

Llama 4 Maverick

Not sourced

Mercury Edit 2

Not sourced

Provider availability

Llama 4 Maverick

Not sourced

Mercury Edit 2

Not sourced

Reasoning profile

Llama 4 Maverick

Non-Reasoning

Mercury Edit 2

Non-Reasoning

Weight access

Llama 4 Maverick

Open Weight

Mercury Edit 2

Proprietary

License

Llama 4 Maverick

Open Weight

Mercury Edit 2

Proprietary

Release date

Llama 4 Maverick

2026-02-28

Mercury Edit 2

2026-03-30

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Llama 4 Maverick has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Llama 4 Maverick
API / mo$0
Self-host / mo$2,610
Break-even—
Mercury Edit 2
API / mo$750
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence1 rows

Math

  • FrontierMath v2 (Tiers 1-3)

    Llama 4 Maverick0.690%
    Source
    Mercury Edit 2—

    Not directly comparable

Frequently asked questions

Which is better, Llama 4 Maverick or Mercury Edit 2?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Llama 4 Maverick or Mercury Edit 2?

Mercury Edit 2 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Llama 4 Maverick or Mercury Edit 2?

Mercury Edit 2 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Llama 4 Maverick or Mercury Edit 2?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Llama 4 Maverick or Mercury Edit 2?

Llama 4 Maverick has the larger documented context window: 1M, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 10, 2026

Watch Llama 4 Maverick vs Mercury Edit 2

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.