Claude Opus 4.8 vs Gemini 3 Flash
At a Glance
| Compare | Claude Opus 4.8Anthropic | Gemini 3 FlashGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #18 of 4670.1 score · 3/3 sources · complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #42 of 44$0.604 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #35 of 3840.5 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $0.50Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $3.00Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,049K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Claude Opus 4.8 | Gemini 3 Flash |
|---|---|---|
| LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · leader | 1,464.07100% of row best · rating · claude-opus-4-8; 95% CI [1457.10320334, 1471.03216030]; votes 12128; rank 19 | 1,412.9997% of row best · rating · gemini-3-flash; 95% CI [1403.58694998, 1422.40270038]; votes 7158; rank 40 |
| LMArena Search Arenasearch-2026-08-24-d25aabda0010 · arena_rating · statistical tie | 1,204.30100% of row best · rating · claude-opus-4-8; 95% CI [1197.89112684, 1210.71069451]; votes 70998; rank 12 | 1,198.0999% of row best · rating · gemini-3-flash-grounding; 95% CI [1193.35426288, 1202.82591975]; votes 149334; rank 15 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,452.66100% of row best · rating · claude-opus-4-8; 95% CI [1448.52490690, 1456.79817098]; votes 53446; rank 40 | 1,442.4099% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1439.30492660, 1445.49388279]; votes 85799; rank 61 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,288.23100% of row best · rating · claude-opus-4-8; 95% CI [1281.27991800, 1295.18871241]; votes 15801; rank 25 | 1,265.3798% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1259.84136462, 1270.89646969]; votes 34860; rank 41 |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 3 benchmark winsNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Opus 4.8 | Gemini 3 Flash |
|---|---|---|
| Developer | Anthropic | Google DeepMind |
| Family | Claude 4 8 | Gemini 3 |
| Model | Claude Opus 4.8 | Gemini 3 Flash |
| Version | Claude Opus 4.8 | Gemini 3 Flash |
| Lifecycle | active | preview |
| Released | 2026-05-28 | Unknown |
| Knowledge cutoff | 2026-01-01 | Unknown |
| Input modalities | Text, Image | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,049K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Claude Opus 4.8 Capabilities
Gemini 3 Flash Capabilities
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.8 vs Gemini 3 Flash FAQs
Is Claude Opus 4.8 or Gemini 3 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.8 and Gemini 3 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.8 or Gemini 3 Flash?+
Claude Opus 4.8 is $5.00 and Gemini 3 Flash is $0.50 per million tokens, so Gemini 3 Flash is cheaper on this metric. Claude Opus 4.8 is $25.00 and Gemini 3 Flash is $3.00 per million tokens, so Gemini 3 Flash is cheaper on this metric.
Which has a larger context window, Claude Opus 4.8 or Gemini 3 Flash?+
Gemini 3 Flash has the larger sourced context window. Claude Opus 4.8 supports 1,000K and Gemini 3 Flash supports 1,049K.
Which performs better in benchmarks, Claude Opus 4.8 or Gemini 3 Flash?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Claude Opus 4.8 or Gemini 3 Flash be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Opus 4.8 is not marked open weight; Gemini 3 Flash is not marked open weight.
Can Claude Opus 4.8 and Gemini 3 Flash understand images?+
Claude Opus 4.8 is documented with image input; Gemini 3 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.8 or Gemini 3 Flash?+
Claude Opus 4.8 has the larger sourced maximum output: Claude Opus 4.8 supports 128K and Gemini 3 Flash supports 66K output tokens.
Do Claude Opus 4.8 and Gemini 3 Flash support reasoning and tool use?+
Claude Opus 4.8: reasoning, tool calling, and image input. Gemini 3 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.8 or Gemini 3 Flash?+
Claude Opus 4.8 has 2 sourced provider routes; Gemini 3 Flash has 2, a tie.
Which offers better value, Claude Opus 4.8 or Gemini 3 Flash?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.