Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Anthropic: Claude Opus 4.7 (batch) vs DeepSeek Coder V2 benchmark

Name: Anthropic: Claude Opus 4.7 (batch) vs DeepSeek Coder V2 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Anthropic: Claude Opus 4.7 (batch) (Anthropic) and DeepSeek Coder V2 (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. DeepSeek Coder V2 wins on output price at $0.28/1M. Anthropic: Claude Opus 4.7 (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 Opus 4.7 (batch)

Auto-discovered from OpenRouter (anthropic/claude-opus-4.7:batch). Preview until a second source matches.

$12.5/1M out

DeepSeek

DeepSeek Coder V2

DeepSeek open-weight Mixture-of-Experts coding model supporting 338 programming languages and 128k context.

Elo 1,365$0.28/1M 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 Opus 4.7 (batch) (1)vsDeepSeek Coder V2 (9)

Anthropic: Claude Opus 4.7 (batch): 1W (10%)Overall: DeepSeek Coder V2DeepSeek Coder V2: 9W (90%)

← Anthropic: Claude Opus 4.7 (batch)DeepSeek Coder V2 →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,365

Coding Elo

—vs1,442

SWE-bench

—vs60.5%

LiveBench

—vs58.6%

GPQA Diamond

—vs70.2%

Anthropic: Claude Opus 4.7 (batch): 0WDeepSeek Coder V2: 5W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs75 tok/s

Time to first token

—vs290 ms

Anthropic: Claude Opus 4.7 (batch): 0WDeepSeek Coder V2: 2W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$12.5/1Mvs$0.28/1M

Input price

$2.5/1Mvs$0.14/1M

Context window

1Mvs128k

Anthropic: Claude Opus 4.7 (batch): 1WDeepSeek Coder V2: 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 AdvantageDeepSeek Coder V2 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

DeepSeek Coder V2

$12.22/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,365

Code Elo

High is better

—

Code EloHigh is better

1,442

LiveBench

High is better

—

LiveBenchHigh is better

58.6%

SWE-bench

High is better

—

SWE-benchHigh is better

60.5%

GPQA

High is better

—

GPQAHigh is better

70.2%

TTFT

Low is better

—

TTFTLow is better

290 ms

Speed

High is better

—

SpeedHigh is better

75 tok/s

In $

Low is better

$2.5/1M

In $Low is better

$0.14/1M+1686%

Out $

Low is better

$12.5/1M

Out $Low is better

$0.28/1M+4364%

Context

High is better

+681%1M

ContextHigh is better

128k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 97% with DeepSeek Coder V2

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 Opus 4.7 (batch)$275.00 / mo

In: $87.50Out: $187.50

DeepSeek Coder V2$9.10 / mo

In: $4.90Out: $4.20

Estimated Cost Delta

DeepSeek Coder V2 is estimated to save $265.90/month ($3,191/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
DeepSeek Coder V2:Pick DeepSeek Coder V2 when you are optimizing output cost.
2
Anthropic: Claude Opus 4.7 (batch):Pick Anthropic: Claude Opus 4.7 (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Opus 4.7 (batch)

Larger window (1M).

Screenshots / visionDeepSeek Coder V2

DeepSeek Coder V2 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	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Opus 4.7 (batch)	Larger window (1M).
Screenshots / vision	DeepSeek Coder V2	DeepSeek Coder V2 is the side marked multimodal in the catalog.

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LIVE

Anthropic

Anthropic: Claude Opus 4.7 (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$12.5/1M

DeepSeek

DeepSeek Coder V2

Elo 1,365

LiveBench58.6%

SWE-bench60.5%

Speed75 tok/s

Output cost$0.28/1M

Frequently Asked Questions

Which is better overall, Anthropic: Claude Opus 4.7 (batch) or DeepSeek Coder V2?: 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 Opus 4.7 (batch) or DeepSeek Coder V2?: 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?: DeepSeek Coder V2 output tokens are $0.28/1M versus $12.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Anthropic: Claude Opus 4.7 (batch) or DeepSeek Coder V2?: We do not have TTFT for both models.
Which has the larger context window?: Anthropic: Claude Opus 4.7 (batch) accepts 1M tokens versus 128k.
Can I self-host either model?: DeepSeek Coder V2 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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 Opus 4.7 (batch) and DeepSeek Coder V2 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Anthropic: Claude Opus 4.7 (batch) matchups →|All DeepSeek Coder V2 matchups →

DeepSeek Coder V2 vs DeepSeek V3 (next deepseek)Claude Opus 4.5 vs DeepSeek Coder V2 Claude Opus 4.6 vs DeepSeek Coder V2 Claude Sonnet 4.5 vs DeepSeek Coder V2 DeepSeek V4 Pro vs DeepSeek Coder V2 Claude Opus 5 vs DeepSeek Coder V2

Anthropic: Claude Opus 4.7 (batch) vs DeepSeek Coder V2 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic: Claude Opus 4.7 (batch) (1)vsDeepSeek Coder V2 (9)

Anthropic: Claude Opus 4.7 (batch): 1W (10%)Overall: DeepSeek Coder V2DeepSeek Coder V2: 9W (90%)

← Anthropic: Claude Opus 4.7 (batch)DeepSeek Coder V2 →

DeepSeek Coder V2 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,365

Coding Elo

—vs1,442

SWE-bench

—vs60.5%

LiveBench

—vs58.6%

GPQA Diamond

—vs70.2%

Anthropic: Claude Opus 4.7 (batch): 0WDeepSeek Coder V2: 5W

DeepSeek Coder V2 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs75 tok/s

Time to first token

—vs290 ms

Anthropic: Claude Opus 4.7 (batch): 0WDeepSeek Coder V2: 2W

DeepSeek Coder V2 (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$12.5/1Mvs$0.28/1M

Input price

$2.5/1Mvs$0.14/1M

Context window

1Mvs128k

Anthropic: Claude Opus 4.7 (batch): 1WDeepSeek Coder V2: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatDeepSeek Coder V2

Lower output list price ($0.28/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAnthropic: Claude Opus 4.7 (batch)

Larger window (1M).

Screenshots / visionDeepSeek Coder V2

DeepSeek Coder V2 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	DeepSeek Coder V2	Lower output list price ($0.28/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Anthropic: Claude Opus 4.7 (batch)	Larger window (1M).
Screenshots / vision	DeepSeek Coder V2	DeepSeek Coder V2 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Anthropic: Claude Opus 4.7 (batch) or DeepSeek Coder V2?

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 Opus 4.7 (batch) or DeepSeek Coder V2?

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?

DeepSeek Coder V2 output tokens are $0.28/1M versus $12.5/1M. Input prices and retry rates still move the real bill.

Which is faster, Anthropic: Claude Opus 4.7 (batch) or DeepSeek Coder V2?

We do not have TTFT for both models.

Which has the larger context window?

Anthropic: Claude Opus 4.7 (batch) accepts 1M tokens versus 128k.

Can I self-host either model?

DeepSeek Coder V2 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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 Opus 4.7 (batch) and DeepSeek Coder V2 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.