Claude Opus 5 vs Gemini 3.8 Flash
At a Glance
| Compare | Claude Opus 5Anthropic | Gemini 3.8 FlashGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #3 of 4694.1 score · 3/3 sources · complete | #8 of 4682.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 54.7–88.0 |
| CostLower is better · Published-token output estimate | #39 of 44$0.371 per LiveBench case | #26 of 44$0.160 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #13 of 3857.6 score · 3/3 sources · complete | #8 of 3860.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.7–63.4 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $0.75Google AI ↗ · Sep 2, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $3.75Google AI ↗ · Sep 2, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,049K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 2, 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 5 | Gemini 3.8 Flash |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | 10.16100% of row best · score · Claude Opus 5 (Max); 95% CI [8.61078356, 11.71492901]; sessions 19934; observations 2534849; rank 4 | 4.7195% of row best · score · Gemini 3.8 Flash (High); 95% CI [2.80246501, 6.61533867]; sessions 12534; observations 712246; rank 13 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,504.92100% of row best · rating · claude-opus-5-high; 95% CI [1500.70174969, 1509.13092375]; votes 42617; rank 3 | 1,494.6799% of row best · rating · gemini-3.8-flash-high; 95% CI [1486.13928353, 1503.20869643]; votes 5076; rank 6 |
| LiveBench2026-06-25 · overall · leader | 83.44100% of row best · percent · claude-opus-5-max-effort · 14,826 output tokens / case | 80.8597% of row best · percent · gemini-3.8-flash-high · 42,786 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 88.76100% of row best · points · Claude Opus 5 (max effort) · 9,446 output tokens / case | 77.8288% of row best · points · Gemini 3.8 Flash (high thinking) · 13,616 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 2 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Quality Versus Estimated Output Cost
Side-by-Side Facts
| Field | Claude Opus 5 | Gemini 3.8 Flash |
|---|---|---|
| Developer | Anthropic | Google DeepMind |
| Family | Claude 5 | Gemini 3 |
| Model | Claude Opus 5 | Gemini 3.8 Flash |
| Version | Claude Opus 5 | Gemini 3.8 Flash |
| Lifecycle | active | active |
| Released | 2026-07-24 | 2026-09-02 |
| Knowledge cutoff | Unknown | 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), Openrouter (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, code_execution, computer_use, generation, reasoning, structured_outputs, tools |
Claude Opus 5 Capabilities
Gemini 3.8 Flash Capabilities
Primary Evidence
Sources and Freshness
Questions
Claude Opus 5 vs Gemini 3.8 Flash FAQs
Is Claude Opus 5 or Gemini 3.8 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 5 and Gemini 3.8 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 5 or Gemini 3.8 Flash?+
Claude Opus 5 is $5.00 and Gemini 3.8 Flash is $0.75 per million tokens, so Gemini 3.8 Flash is cheaper on this metric. Claude Opus 5 is $25.00 and Gemini 3.8 Flash is $3.75 per million tokens, so Gemini 3.8 Flash is cheaper on this metric.
Which has a larger context window, Claude Opus 5 or Gemini 3.8 Flash?+
Gemini 3.8 Flash has the larger sourced context window. Claude Opus 5 supports 1,000K and Gemini 3.8 Flash supports 1,049K.
Which performs better in benchmarks, Claude Opus 5 or Gemini 3.8 Flash?+
Claude Opus 5 leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Claude Opus 5 or Gemini 3.8 Flash be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Opus 5 is not marked open weight; Gemini 3.8 Flash is not marked open weight.
Can Claude Opus 5 and Gemini 3.8 Flash understand images?+
Claude Opus 5 is documented with image input; Gemini 3.8 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 5 or Gemini 3.8 Flash?+
Claude Opus 5 has the larger sourced maximum output: Claude Opus 5 supports 128K and Gemini 3.8 Flash supports 66K output tokens.
Do Claude Opus 5 and Gemini 3.8 Flash support reasoning and tool use?+
Claude Opus 5: reasoning, tool calling, and image input. Gemini 3.8 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 5 or Gemini 3.8 Flash?+
Claude Opus 5 has 3 sourced provider routes; Gemini 3.8 Flash has 2, so Claude Opus 5 has broader tracked availability.
Which offers better value, Claude Opus 5 or Gemini 3.8 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.