Qwen3.8 27B vs Gemini 3.5 Flash Lite
At a Glance
| Compare | Qwen3.8 27BQwen | Gemini 3.5 Flash LiteGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #30 of 4654.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.0–69.4 | #39 of 4617.6 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | #16 of 44$0.072 per LiveBench case | #8 of 44$0.029 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #17 of 3854.8 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 45.8–62.5 | #32 of 3846.2 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.20Deepinfra ↗ · Sep 22, 2026 | $0.30Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $2.50Deepinfra ↗ · Sep 22, 2026 | $2.50Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 262K | 1,049K |
| Model facts checked | Aug 28, 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 | Qwen3.8-27B | Gemini 3.5 Flash-Lite |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | -0.64100% of row best · score · Qwen 3.8 27B; 95% CI [-1.36495564, 0.07819043]; sessions 37257; observations 4349219; rank 29 | -15.3585% of row best · score · Gemini 3.5 Flash Lite; 95% CI [-16.65525683, -14.04242266]; sessions 23248; observations 670178; rank 45 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,439.27100% of row best · rating · qwen3.8-27b; 95% CI [1432.84410050, 1445.69542028]; votes 10697; rank 68 | 1,435.54100% of row best · rating · gemini-3.5-flash-lite; 95% CI [1430.59505493, 1440.49024696]; votes 26165; rank 79 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,272.12100% of row best · rating · qwen3.8-27b; 95% CI [1262.21853873, 1282.01179703]; votes 4577; rank 35 | 1,268.42100% of row best · rating · gemini-3.5-flash-lite; 95% CI [1258.88097193, 1277.96729164]; votes 5254; rank 37 |
| LiveBench2026-06-25 · overall · leader | 78.02100% of row best · percent · qwen3.8-27b · 28,740 output tokens / case | 66.3585% of row best · percent · gemini-3.5-flash-lite-high · 11,526 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 2 ties | 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.
Side-by-Side Facts
| Field | Qwen3.8-27B | Gemini 3.5 Flash-Lite |
|---|---|---|
| Developer | Qwen | Google DeepMind |
| Family | Qwen3 8 27b | Gemini 3 |
| Model | Qwen3.8-27B | Gemini 3.5 Flash-Lite |
| Version | Qwen3.8-27B | Gemini 3.5 Flash-Lite |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text |
| Context window | 262K | 1,049K |
| Total parameters | 27.8B | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Qwen3.8 27B Capabilities
Gemini 3.5 Flash Lite Capabilities
Primary Evidence
Sources and Freshness
Questions
Qwen3.8 27B vs Gemini 3.5 Flash Lite FAQs
Is Qwen3.8 27B or Gemini 3.5 Flash Lite better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 27B and Gemini 3.5 Flash Lite, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
Qwen3.8 27B is $0.20 and Gemini 3.5 Flash Lite is $0.30 per million tokens, so Qwen3.8 27B is cheaper on this metric. Qwen3.8 27B is $2.50 and Gemini 3.5 Flash Lite is $2.50 per million tokens, so they are tied on this metric.
Which has a larger context window, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
Gemini 3.5 Flash Lite has the larger sourced context window. Qwen3.8 27B supports 262K and Gemini 3.5 Flash Lite supports 1,049K.
Which performs better in benchmarks, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
Qwen3.8 27B leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Qwen3.8 27B or Gemini 3.5 Flash Lite be self-hosted?+
Qwen3.8 27B is the only model in this pair currently marked as self-hostable. Qwen3.8 27B is open weight; Gemini 3.5 Flash Lite is not marked open weight.
Can Qwen3.8 27B and Gemini 3.5 Flash Lite understand images?+
Qwen3.8 27B is documented with image input; Gemini 3.5 Flash Lite is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
Qwen3.8 27B has the larger sourced maximum output: Qwen3.8 27B supports 131K and Gemini 3.5 Flash Lite supports 66K output tokens.
Do Qwen3.8 27B and Gemini 3.5 Flash Lite support reasoning and tool use?+
Qwen3.8 27B: reasoning, tool calling, and image input. Gemini 3.5 Flash Lite: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
Qwen3.8 27B has 3 sourced provider routes; Gemini 3.5 Flash Lite has 2, so Qwen3.8 27B has broader tracked availability.
Which offers better value, Qwen3.8 27B or Gemini 3.5 Flash Lite?+
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.