Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

Anthropic: Claude Sonnet 4.5 (batch) vs Codestral 25.01 benchmark

Name: Anthropic: Claude Sonnet 4.5 (batch) vs Codestral 25.01 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Anthropic: Claude Sonnet 4.5 (batch) (Anthropic) and Codestral 25.01 (Mistral) using the latest snapshots we have as of Aug 16, 2026. Codestral 25.01 wins on output price at $0.9/1M. Anthropic: Claude Sonnet 4.5 (batch) has the larger context window (1M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Anthropic

Anthropic: Claude Sonnet 4.5 (batch)

Auto-discovered from OpenRouter (anthropic/claude-sonnet-4.5:batch). Preview until a second source matches.

$7.5/1M out

Mistral

Codestral 25.01

Mistral code-specialist model.

Elo 1,320$0.9/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic: Claude Sonnet 4.5 (batch) (1)vsCodestral 25.01 (9)

Anthropic: Claude Sonnet 4.5 (batch): 1W (10%)Overall: Codestral 25.01Codestral 25.01: 9W (90%)

← Anthropic: Claude Sonnet 4.5 (batch)Codestral 25.01 →

Codestral 25.01 (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,320

Coding Elo

—vs1,402

SWE-bench

—vs51.8%

LiveBench

—vs54%

GPQA Diamond

—vs58.4%

Anthropic: Claude Sonnet 4.5 (batch): 0WCodestral 25.01: 5W

Codestral 25.01 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs148 tok/s

Time to first token

—vs150 ms

Anthropic: Claude Sonnet 4.5 (batch): 0WCodestral 25.01: 2W

Codestral 25.01 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$7.5/1Mvs$0.9/1M

Input price

$1.5/1Mvs$0.3/1M

Context window

1Mvs256k

Anthropic: Claude Sonnet 4.5 (batch): 1WCodestral 25.01: 2W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageCodestral 25.01 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Codestral 25.01

$6.60/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,320

Code Elo

High is better

—

Code EloHigh is better

1,402

LiveBench

High is better

—

LiveBenchHigh is better

54%

SWE-bench

High is better

—

SWE-benchHigh is better

51.8%

GPQA

High is better

—

GPQAHigh is better

58.4%

TTFT

Low is better

—

TTFTLow is better

150 ms

Speed

High is better

—

SpeedHigh is better

148 tok/s

In $

Low is better

$1.5/1M

In $Low is better

$0.3/1M+400%

Out $

Low is better

$7.5/1M

Out $Low is better

$0.9/1M+733%

Context

High is better

+291%1M

ContextHigh is better

256k

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 85% with Codestral 25.01

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Anthropic: Claude Sonnet 4.5 (batch)$165.00 / mo

In: $52.50Out: $112.50

Codestral 25.01$24.00 / mo

In: $10.50Out: $13.50

Estimated Cost Delta

Codestral 25.01 is estimated to save $141.00/month ($1,692/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Codestral 25.01:Pick Codestral 25.01 when you are optimizing output cost.
2
Anthropic: Claude Sonnet 4.5 (batch):Pick Anthropic: Claude Sonnet 4.5 (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatCodestral 25.01

Lower output list price ($0.9/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Sonnet 4.5 (batch)

Larger window (1M).

Screenshots / visionCodestral 25.01

Codestral 25.01 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Codestral 25.01	Lower output list price ($0.9/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Sonnet 4.5 (batch)	Larger window (1M).
Screenshots / vision	Codestral 25.01	Codestral 25.01 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJan 14, 2025

Codestral 25.01: Mistral’s code-specialist row

Jan 2025 code model. Still a valid cheap-coding compare. Not a chatbot.

Community Sentiment

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LIVE

Anthropic

Anthropic: Claude Sonnet 4.5 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$7.5/1M

Mistral

Codestral 25.01

Elo 1,320

LiveBench54%

SWE-bench51.8%

Speed148 tok/s

Output cost$0.9/1M

Frequently Asked Questions

Which is better overall, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Codestral 25.01 output tokens are $0.9/1M versus $7.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?: We do not have TTFT for both models.
Which has the larger context window?: Anthropic: Claude Sonnet 4.5 (batch) accepts 1M tokens versus 256k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Anthropic: Claude Sonnet 4.5 (batch) and Codestral 25.01 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Anthropic: Claude Sonnet 4.5 (batch) matchups →|All Codestral 25.01 matchups →

Codestral 25.01 vs Mistral Large 3 (next mistral)Claude Opus 4.5 vs Codestral 25.01 Claude Opus 4.6 vs Codestral 25.01 Claude Sonnet 4.5 vs Codestral 25.01 Claude Opus 5 vs Codestral 25.01 Claude Fable 5 vs Codestral 25.01

Anthropic: Claude Sonnet 4.5 (batch) vs Codestral 25.01 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic: Claude Sonnet 4.5 (batch) (1)vsCodestral 25.01 (9)

Anthropic: Claude Sonnet 4.5 (batch): 1W (10%)Overall: Codestral 25.01Codestral 25.01: 9W (90%)

← Anthropic: Claude Sonnet 4.5 (batch)Codestral 25.01 →

Codestral 25.01 (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,320

Coding Elo

—vs1,402

SWE-bench

—vs51.8%

LiveBench

—vs54%

GPQA Diamond

—vs58.4%

Anthropic: Claude Sonnet 4.5 (batch): 0WCodestral 25.01: 5W

Codestral 25.01 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs148 tok/s

Time to first token

—vs150 ms

Anthropic: Claude Sonnet 4.5 (batch): 0WCodestral 25.01: 2W

Codestral 25.01 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$7.5/1Mvs$0.9/1M

Input price

$1.5/1Mvs$0.3/1M

Context window

1Mvs256k

Anthropic: Claude Sonnet 4.5 (batch): 1WCodestral 25.01: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatCodestral 25.01

Lower output list price ($0.9/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Sonnet 4.5 (batch)

Larger window (1M).

Screenshots / visionCodestral 25.01

Codestral 25.01 is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Codestral 25.01	Lower output list price ($0.9/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Sonnet 4.5 (batch)	Larger window (1M).
Screenshots / vision	Codestral 25.01	Codestral 25.01 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Codestral 25.01 output tokens are $0.9/1M versus $7.5/1M. Input prices and retry rates still move the real bill.

Which is faster, Anthropic: Claude Sonnet 4.5 (batch) or Codestral 25.01?

We do not have TTFT for both models.

Which has the larger context window?

Anthropic: Claude Sonnet 4.5 (batch) accepts 1M tokens versus 256k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Anthropic: Claude Sonnet 4.5 (batch) and Codestral 25.01 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

Codestral 25.01

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Codestral 25.01: Mistral’s code-specialist row

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Anthropic: Claude Sonnet 4.5 (batch)

Codestral 25.01

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

Codestral 25.01

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Codestral 25.01: Mistral’s code-specialist row

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Anthropic: Claude Sonnet 4.5 (batch)

Codestral 25.01

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons