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  3. Claude Opus 4.6 vs Google: Gemini 3.5 Flash (batch)

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

Claude Opus 4.6 vs Google: Gemini 3.5 Flash (batch) benchmark

This page compares Claude Opus 4.6 (Anthropic) and Google: Gemini 3.5 Flash (batch) (Google) using the latest snapshots we have as of Aug 17, 2026. Google: Gemini 3.5 Flash (batch) wins on output price at $4.5/1M. Google: Gemini 3.5 Flash (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.

Quick answer

Claude Opus 4.6 vs Google: Gemini 3.5 Flash (batch) is a dated snapshot, not a lab score. Google: Gemini 3.5 Flash (batch) is the cheaper output token. Elo is crowd preference, not an exam. Pick the column that matches the job.
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Anthropic

Claude Opus 4.6

Follow-on Opus release. Slightly behind 4.5 on official SWE-bench bash-only in the last published sweep; stronger long-horizon agent traces.

Opus 4.6Elo 1,574$25/1M out

Google

Google: Gemini 3.5 Flash (batch)

Auto-discovered from OpenRouter (google/gemini-3.5-flash:batch). Preview until a second source matches.

$4.5/1M out
Model Lineage & Multi-Tier Derivatives🇺🇸 US Frontier

Claude 4 Series Family (5 models)

Compare vs Base (Claude Opus 4.5)
Claude Opus 4.5
Anthropic
Flagship Base
CoT Scaler
Elo
1568
Speed
62 tok/s
Price
$25.00 / 1M
View model →vs this
Claude Opus 4.6
Anthropic
Opus 4.6
CoT Scaler
Elo
1574
Speed
64 tok/s
Price
$25.00 / 1M
+6 Elo0% cost
Viewing now
Claude Sonnet 4.5
Anthropic
Sonnet 4.5
Elo
1524
Speed
88 tok/s
Price
$15.00 / 1M
-44 Elo-40% cost1.4x speed
View model →vs this
Claude Opus 4.8
Anthropic
Opus 4.8
CoT Scaler
Elo
1598
Speed
66 tok/s
Price
$25.00 / 1M
+30 Elo0% cost1.1x speed
View model →vs this
Claude Haiku 4.5
Anthropic
Haiku 4.5
Elo
1438
Speed
175 tok/s
Price
$5.00 / 1M
-130 Elo-80% cost2.8x speed
View model →vs this
Claude Opus 4.6 Inference Compute Profile
Inference-Time Compute & Reasoning EffortDynamic CoT

Claude Opus 4.6 Reasoning Scaler & Token Billing Simulator

Param: thinking_budget

Reasoning models scale test-time compute by generating hidden chain-of-thought (CoT) tokens. These tokens are billed at standard output rates and directly expand latency (TTFT) in exchange for higher GPQA Diamond and SWE-bench Verified problem resolve rates.

Estimated TTFT
360 ms
1.0x (Standard eval)
CoT Thinking Tokens
~3,200
Billed as output tokens
Est. Cost / 1k Calls
$90.00
9.0x base invoice
STEM / SWE Boost
+5.2%
GPQA & SWE-bench scaling
Medium (16k budget) Operational Profile

Official evaluation benchmark budget for SWE-bench and LiveBench.

Direct Provider APIAnthropic
"thinking": {
  "type": "enabled",
  "budget_tokens": 16384
}
OpenRouter Unified APIUnified Gateway
"reasoning": {
  "effort": "medium",
  "max_tokens": 3200
}

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A
Model B
Quick vs:vs Claude Opus 4.5vs Claude Sonnet 4.5vs Claude 3.7 Sonnetvs GPT-5

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Opus 4.6 (7)vsGoogle: Gemini 3.5 Flash (batch) (3)
Claude Opus 4.6: 7W (70%)Overall: Claude Opus 4.6Google: Gemini 3.5 Flash (batch): 3W (30%)
← Claude Opus 4.6Google: Gemini 3.5 Flash (batch) →
Claude Opus 4.6 (5/5)

Intelligence & Reasoning

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

Preference Elo
1,574vs—
Coding Elo
1,570vs—
SWE-bench
75.9%vs—
LiveBench
72%vs—
GPQA Diamond
84.8%vs—
Claude Opus 4.6: 5WGoogle: Gemini 3.5 Flash (batch): 0W
Claude Opus 4.6 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed
64 tok/svs—
Time to first token
360 msvs—
Claude Opus 4.6: 2WGoogle: Gemini 3.5 Flash (batch): 0W
Google: Gemini 3.5 Flash (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price
$25/1Mvs$4.5/1M
Input price
$5/1Mvs$0.75/1M
Context window
1Mvs1M
Claude Opus 4.6: 0WGoogle: Gemini 3.5 Flash (batch): 3W
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 AdvantageClaude Opus 4.6 4/6
Preference Elo

No shared data

No shared data

Throughput Speed

No shared data

No shared data

Token Price Efficiency

Google: Gemini 3.5 Flash (batch)

$20.50/1M cheaper

Full Benchmark Score Matrix

—
Elo
High is better
1,574
EloHigh is better
—
Code Elo
High is better
1,570
Code EloHigh is better
—
LiveBench
High is better
72%
LiveBenchHigh is better
—
SWE-bench
High is better
75.9%
SWE-benchHigh is better
—
GPQA
High is better
84.8%
GPQAHigh is better
—
TTFT
Low is better
360 ms
TTFTLow is better
—
Speed
High is better
64 tok/s
SpeedHigh is better
—
In $
Low is better
$5.00 / 1M
In $Low is better
$0.75 / 1M+567%
Out $
Low is better
$25.00 / 1M
Out $Low is better
$4.50 / 1M+456%
Context
High is better
1M
ContextHigh is better
1M+5%
Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 83% with Google: Gemini 3.5 Flash (batch)
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Claude Opus 4.6$550.00 / mo
In: $175Out: $375
Google: Gemini 3.5 Flash (batch)$93.75 / mo
In: $26.25Out: $67.5
Estimated Cost Delta

Google: Gemini 3.5 Flash (batch) is estimated to save $456.25/month ($5,475/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Google: Gemini 3.5 Flash (batch):Pick Google: Gemini 3.5 Flash (batch) when you are optimizing output cost.
  • 2
    Google: Gemini 3.5 Flash (batch):Pick Google: Gemini 3.5 Flash (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGoogle: Gemini 3.5 Flash (batch)

Lower output list price ($4.5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGoogle: Gemini 3.5 Flash (batch)

Larger window (1M).

Screenshots / visionClaude Opus 4.6

Claude Opus 4.6 is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatGoogle: Gemini 3.5 Flash (batch)Lower output list price ($4.5/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGGoogle: Gemini 3.5 Flash (batch)Larger window (1M).
Screenshots / visionClaude Opus 4.6Claude Opus 4.6 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news
launchMay 10, 2026

Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Slightly behind 4.5 on one official SWE-bench sweep; stronger long-horizon traces. We keep the row for old vs URLs.

Community Sentiment

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LIVE
VS
Anthropic

Claude Opus 4.6

Elo 1,574
LiveBench72%
SWE-bench75.9%
Speed64 tok/s
Output cost$25/1M
Google

Google: Gemini 3.5 Flash (batch)

Elo n/a
LiveBench—
SWE-bench—
Speed—
Output cost$4.5/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4.6 or Google: Gemini 3.5 Flash (batch)?
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, Claude Opus 4.6 or Google: Gemini 3.5 Flash (batch)?
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?
Google: Gemini 3.5 Flash (batch) output tokens are $4.5/1M versus $25/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4.6 or Google: Gemini 3.5 Flash (batch)?
We do not have TTFT for both models.
Which has the larger context window?
Google: Gemini 3.5 Flash (batch) accepts 1M tokens versus 1M.
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. Claude Opus 4.6 and Google: Gemini 3.5 Flash (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · May 10, 2026

    Claude Opus 4.6: the May follow-on that still shows up in old bookmarks

Similar Head-to-Head Comparisons

All Claude Opus 4.6 matchups →|All Google: Gemini 3.5 Flash (batch) matchups →
Claude Opus 4.6 vs Claude Opus 4.5 (previous opus)Claude Opus 4.6 vs Claude Opus 4.8 (next opus)Gemini 3.6 Pro vs Claude Opus 4.6Claude Sonnet 5 vs Claude Opus 4.6Gemini 3 Pro vs Claude Opus 4.6Claude Fable 5 vs Claude Opus 4.6