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BenchLM

Claude Sonnet 5.5 vs Mistral Large 3

Updated September 28, 2026. Rank says Claude Sonnet 5.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

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.

Model A
Anthropic logo
Claude Sonnet 5.5

Anthropic

80.49/100

Estimated · Public rank #5

90% interval 69.0–92.0

Model B
Mistral logo
Mistral Large 3

Mistral

34.13/100

Estimated · Public rank #139

90% interval 8.7–59.5

Shared results
0
Claude Sonnet 5.5 only
47
Mistral Large 3 only
0
Like-for-like categories
0 / 8
Estimated: Claude Sonnet 5.5 and Mistral Large 3How 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.

  • Long documents

    Prompts that approach the documented context limit

    Claude Sonnet 5.5

    Claude Sonnet 5.5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Mistral Large 3

    Mistral Large 3 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

    Mistral Large 3

    Mistral Large 3 has the lower estimated token cost for this stated workload. Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback
Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    Mistral Large 3

    Mistral Large 3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Claude Sonnet 5.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Mistral Large 3 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

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.

79.6Claude Sonnet 5.518.4Mistral Large 3

Directional only · BenchAlign v5.7

Claude Sonnet 5.5 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.

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

Open the coding leaderboardShortlist models for this job
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.

3 categories rest 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.

A shared-evidence shape is not available.

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

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 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

Directional only
Claude Sonnet 5.5
66.1
Supported · #10/111
Mistral Large 3
16.4
Estimated · #100/111
Basis
BenchAlign v5.7 lane · 11 vs 0 public rows
Reading
Directional only

Coding

Directional only
Claude Sonnet 5.5
79.6
Estimated · #3/136
Mistral Large 3
18.4
Supported · #126/136
Basis
BenchAlign v5.7 lane · 9 vs 0 public rows
Reading
Directional only

Knowledge

Directional only
Claude Sonnet 5.5
80.9
Supported · #6/160
Mistral Large 3
33.7
Estimated · #115/160
Basis
BenchAlign v5.7 lane · 16 vs 0 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Sonnet 5.5
79.2
#7/27
Mistral Large 3
46.9
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 5.5
83.3
Unranked · 7 rankable rows
Mistral Large 3
43.2
Unranked · 1 rankable row
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5.5
Not ranked
Mistral Large 3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5.5
Not ranked
Mistral Large 3
40.0
#101/124
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5.5
Not ranked
Mistral Large 3
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 v5.7) 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

Claude Sonnet 5.5
$0.007
Fits in one request
Mistral Large 3
$0.00125
Fits in one request

Mistral Large 3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5.5
$0.13
Fits in one request
Mistral Large 3
$0.0295
Fits in one request

Mistral Large 3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Claude Sonnet 5.5
$0.18
Fits in one request
Mistral Large 3
$0.125
Fits in one request
Cached input priced at the published list-input rate

Mistral Large 3 has the lower modeled cost

Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

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.

Cached-input rate

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

Claude Sonnet 5.5

$0.2 per 1M cached input tokens

Claude API pricing

Mistral Large 3

Not published

Reasoning profile

Claude Sonnet 5.5

Reasoning

Mistral Large 3

Non-Reasoning

Weight access

Claude Sonnet 5.5

Proprietary

Mistral Large 3

Proprietary

License

Claude Sonnet 5.5

Proprietary

Mistral Large 3

Proprietary

Release date

Claude Sonnet 5.5

2026-09-28

Mistral Large 3

2025-12-02

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
Repository review: $0.13 vs $0.0295. Cache-heavy agent loop: $0.18 vs $0.125.
Context tradeoff
Claude Sonnet 5.5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Sonnet 5.5 or Mistral Large 3?

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, Claude Sonnet 5.5 or Mistral Large 3?

Claude Sonnet 5.5 scores higher for coding on the public lane, 79.6 to 18.4. Claude Sonnet 5.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Sonnet 5.5 or Mistral Large 3?

Claude Sonnet 5.5 scores higher for agentic tasks on the public lane, 66.1 to 16.4. Mistral Large 3 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Sonnet 5.5 or Mistral Large 3?

For the stated presets, chat costs $0.007 on Claude Sonnet 5.5 and $0.00125 on Mistral Large 3; repository review costs $0.13 and $0.0295; the cache-heavy agent loop costs $0.18 and $0.125. Mistral Large 3 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 5.5 or Mistral Large 3?

Claude Sonnet 5.5 has the larger documented context window: 1M, compared with 256K.

Self-host vs API cost

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

Claude Sonnet 5.5
API / mo$9,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Mistral Large 3
API / mo$1,500
Self-host / mo$9,110
Break-even380M/day
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 evidence47 rows

Agentic

  • Terminal-Bench 4.0

    Claude Sonnet 5.570.60%
    Source
    Mistral Large 3—

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 5.564.5%
    Source
    Mistral Large 3—

    Not directly comparable

  • DRACO

    Claude Sonnet 5.587.0%
    Source
    Mistral Large 3—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Sonnet 5.559.9%
    Source
    Mistral Large 3—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Sonnet 5.510.0%
    Source
    Mistral Large 3—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Sonnet 5.593.1%
    Source
    Mistral Large 3—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Sonnet 5.585.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Sonnet 5.568.5%
    Source
    Mistral Large 3—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Sonnet 5.531.6 turns
    Source
    Mistral Large 3—

    Not directly comparable

  • AutomationBench (Zapier 1.0.6)

    Claude Sonnet 5.544.7%
    Source
    Mistral Large 3—

    Not directly comparable

  • Toolathlon-Verified

    Claude Sonnet 5.577.8%
    Source
    Mistral Large 3—

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Claude Sonnet 5.546.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • cursorBench40

    Claude Sonnet 5.555.5%
    Source
    Mistral Large 3—

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 5.581.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • SWE Multilingual

    Claude Sonnet 5.590.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 5.554.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • DeepSWE

    Claude Sonnet 5.571.0%
    Source
    Mistral Large 3—

    Not directly comparable

  • FrontierCode 1.1 Extended

    Claude Sonnet 5.559.1%
    Source
    Mistral Large 3—

    Not directly comparable

  • ProgramBench

    Claude Sonnet 5.579.7%
    Source
    Mistral Large 3—

    Not directly comparable

  • FrontierSWE v2

    Claude Sonnet 5.561.9%
    Source
    Mistral Large 3—

    Not directly comparable

Multimodal

  • Chartography (no tools)

    Claude Sonnet 5.561.6%
    Source
    Mistral Large 3—

    Not directly comparable

  • Chartography (tools)

    Claude Sonnet 5.590.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Sonnet 5.50.747
    Source
    Mistral Large 3—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Sonnet 5.50.963
    Source
    Mistral Large 3—

    Not directly comparable

  • Biomedical image analysis

    Claude Sonnet 5.572.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • OfficeQA

    Claude Sonnet 5.576.9%
    Source
    Mistral Large 3—

    Not directly comparable

  • OfficeQA Pro

    Claude Sonnet 5.565.6%
    Source
    Mistral Large 3—

    Not directly comparable

Knowledge

  • HealthBench (raw)

    Claude Sonnet 5.569.4%
    Source
    Mistral Large 3—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Sonnet 5.565.4%
    Source
    Mistral Large 3—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Sonnet 5.577.1%
    Source
    Mistral Large 3—

    Not directly comparable

  • HealthBench Professional

    Claude Sonnet 5.569.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Sonnet 5.589.2%
    Source
    Mistral Large 3—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Sonnet 5.544.7%
    Source
    Mistral Large 3—

    Not directly comparable

  • SpatialBench Verified

    Claude Sonnet 5.572.5%
    Source
    Mistral Large 3—

    Not directly comparable

  • SingleCellBench

    Claude Sonnet 5.559.1%
    Source
    Mistral Large 3—

    Not directly comparable

  • Protein Design

    Claude Sonnet 5.551.0%
    Source
    Mistral Large 3—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Sonnet 5.525.0%
    Source
    Mistral Large 3—

    Not directly comparable

  • Medicinal chemistry

    Claude Sonnet 5.565.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • Protein Design library ranking

    Claude Sonnet 5.554.8%
    Source
    Mistral Large 3—

    Not directly comparable

  • De novo protein-binder design

    Claude Sonnet 5.582.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Sonnet 5.567.3%
    Source
    Mistral Large 3—

    Not directly comparable

  • Protocols (understanding)

    Claude Sonnet 5.566.6%
    Source
    Mistral Large 3—

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 5.556.9%
    Source
    Mistral Large 3—

    Not directly comparable

Multilingual

  • GMMLU

    Claude Sonnet 5.592.1%
    Source
    Mistral Large 3—

    Not directly comparable

  • MILU

    Claude Sonnet 5.591.6%
    Source
    Mistral Large 3—

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Sonnet 5.586.8%
    Source
    Mistral Large 3—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Sonnet 5.595.2%
    Source
    Mistral Large 3—

    Not directly comparable

47 public results · 0 shared

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Last updated September 28, 2026