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Compare performance benchmarks, coding intelligence, reasoning evaluations, context limits, and API economics between Qwen3.8 Flash (Alibaba) and Gemini 4 Argon (Google DeepMind).
| Metric / Capability | Qwen3.8 Flash | Gemini 4 Argon |
|---|---|---|
| Developer / Organization | Alibaba | Google DeepMind |
| Release Date | 2026-08-26 | 2026-10-13 |
| Deployment / Weights | Open Weights | Proprietary Cloud API |
| Context Window | 1M tokens (1,000,000 tokens) | 1.0M tokens (1,048,576 tokens) |
| Input Pricing (/1M Tokens) | Free (Open Weights) | $2 |
| Output Pricing (/1M Tokens) | Free (Open Weights) | $10 |
| Benchmark / Domain | Qwen3.8 Flash | Gemini 4 Argon | Advantage |
|---|---|---|---|
Artificial Analysis Intelligence Index Composite index aggregating 10+ evaluations of general reasoning and knowledge. | — | 52.6% | — |
Artificial Analysis Coding Agent Index v2.0 Composite index of coding-agent systems (model + harness) across FrontierCode v1.1, SWE-Atlas-QnA, and Terminal-Bench v4. | — | 53.2% | — |
Terminal-Bench 4.0 Sandboxed command-line tasks requiring shell and file-system operation. | — | 57.4% | — |
ARC-AGI-2 Novel visual grid puzzles requiring abstract rule induction. | — | 91.3% | — |
FrontierMath v2 (Tiers 1-3) Unpublished, research-level mathematics problems across Tiers 1-3. | — | 86.0% | — |
Design Arena ELO Human-preference ELO across UI, 3D, data-visualization, and game-dev generations. | — | 1438 | — |
Both models perform neck-and-neck across available benchmarks, with Qwen3.8 Flash and Gemini 4 Argon each excelling in distinct tasks.
Gemini 4 Argon has the larger context capacity of 1.0M tokens (1,048,576 tokens), compared to 1M tokens for Qwen3.8 Flash.
Qwen3.8 Flash is more cost-effective. Input tokens cost $Free (Open Weights)/M tokens vs $2/M tokens for Gemini 4 Argon.
Qwen3.8 Flash is an open-weights model. Gemini 4 Argon is a proprietary cloud API.
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