"Flash" means something different at each lab. DeepSeek V4 Flash (April 24, 2026): 284B MoE, MIT-licensed, self-hostable, $0.28/1M output. 91.6% LiveCodeBench. Text-only. Gemini 3 Flash (December 12, 2025): Google's multimodal speed tier, $3.00/1M output. Native image, video, and audio input. 65.1% OSWorld. One is the open-weight value titan — 10.7× cheaper, stronger on algorithms and reasoning. The other is the multimodal generalist — weaker on pure code but versed in vision, video, and computer use. Here's the complete data. Test both on CodingFleet.
📊 Key Findings
- Flash leads coding + reasoning: Pro +3.0, GPQA +6.9, MCP Atlas +7.0. For pure code and reasoning tasks, DeepSeek V4 Flash is the stronger model — despite being 10.7× cheaper and five months newer.
- Gemini leads terminal tasks + computer use: Terminal-Bench 58.0% vs 56.9%*, OSWorld 65.1%. *Caution: different benchmark versions (2.1 vs 2.0). Gemini has verified computer use capability; Flash has none published.
- Flash is 10.7× cheaper: $0.28 vs $3.00 per 1M output. MIT-licensed and self-hostable. Gemini is proprietary API-only. For high-volume pipelines, the savings are measured in thousands per month.
- Gemini is natively multimodal: text + image + video + audio. Code from screenshots, video walkthroughs, audio dictation. Flash is text-only. For visual coding workflows, Gemini is the only option.
- Both have 1M context. Flash has 384K max output vs Gemini's 65K — nearly 6× more headroom for large generations.
Compare models on your own code at CodingFleet — 20+ LLMs, side-by-side. See the SWE-bench Pro leaderboard and Terminal-Bench leaderboard for full rankings. Also see: V4 Flash vs GPT-5.4 Mini.
Benchmark Comparison
| Benchmark | DeepSeek V4 Flash | Gemini 3 Flash | Winner |
|---|---|---|---|
| SWE-bench Pro | 52.6% | 49.6% | Flash (+3.0) |
| SWE-bench Verified | 79.0% | 72.0% | Flash (+7.0) |
| Terminal-Bench | 56.9% (2.0) | 58.0% (2.1) | ⚠ Different versions |
| LiveCodeBench | 91.6% | — | Flash |
| Codeforces Rating | 3052 | — | Flash |
| GPQA Diamond | 88.1% | 81.2% | Flash (+6.9) |
| HLE | 34.8% | — | Flash |
| HMMT 2026 Feb | 94.8% | — | Flash |
| MMLU-Pro | 86.2% | — | Flash |
| MCP Atlas (tool use) | 69.0% | 62.0% | Flash (+7.0) |
| Toolathlon | 47.8% | 49.4% | Gemini (+1.6) |
| OSWorld-Verified | — | 65.1% | Gemini |
| MMMU-Pro (multimodal) | — | 81.2% | Gemini |
| CharXiv (chart reasoning) | — | 80.3% | Gemini |
| Output Price /1M tok | $0.28 | $3.00 | Flash (10.7× cheaper) |
| Input Price /1M tok | $0.14 | $0.50 | Flash (3.6× cheaper) |
| Context Window | 1M | 1M | Tie |
| Max Output | 384K | 65K | Flash (5.9×) |
| License | MIT (open-weight) | Proprietary | Flash |
| Self-hosting | Yes | No | Flash |
| Multimodal Input | Text only | Text + Image + Video + Audio | Gemini |
Sources: DeepSeek V4 Model Card — Flash scores (Max reasoning) · Google Model Card (Gemini 3.5 Flash page) — Gemini 3 Flash scores from comparison table · GPQA Diamond: Flash from DS card, Gemini from Artificial Analysis. "—" means not published. Terminal-Bench: Flash uses 2.0 (vendor-reported), Gemini uses 2.1 (Google model card). Not directly comparable.
Capability Radar: Coding vs Multimodal
The radar reveals the fundamental asymmetry between these two Flash-tier models. DeepSeek's blue ring dominates on every coding and reasoning axis — Pro, GPQA, MCP Atlas. The context window is a tie (both 1M), and max output is a blowout (384K vs 65K). Gemini's red ring only appears on the OSWorld axis — the one area Flash cannot touch: computer use. This isn't a close comparison. It's a coding specialist vs a multimodal generalist. Two different species of Flash.
Where Each Model Wins at Coding
DeepSeek V4 Flash — The Pure Code Titan
- SWE-bench Pro 52.6% vs 49.6% (+3.0). For real-world GitHub issue resolution, Flash is clearly better. The gap is consistent with Flash's broader coding strength.
- LiveCodeBench 91.6% — elite algorithms. For competitive programming, algorithm design, and data structures, Flash is in the top tier. Gemini has no published LiveCodeBench score.
- GPQA Diamond 88.1% vs 81.2% (+6.9). For scientific computing and graduate-level reasoning, Flash is meaningfully stronger.
- 10.7× cheaper: $0.28 vs $3.00 per 1M output. MIT-licensed, self-hostable. 384K max output vs 65K. For high-volume production pipelines, Flash is the obvious economic choice.
- MCP Atlas 69.0% vs 62.0% (+7.0). For multi-step tool workflows, Flash is dominant. The gap is large enough to matter for agentic coding.
Gemini 3 Flash — The Multimodal Generalist
- Natively multimodal: text, image, video, audio. Code from screenshots. Debug from screen recordings. Dictate code via audio. Process PDFs and charts. Flash is text-only — this is Gemini's decisive advantage.
- OSWorld-Verified 65.1% — verified computer use. Gemini can operate desktop applications, navigate GUIs, and interact with software interfaces. Flash has zero published computer-use capability.
- MMMU-Pro 81.2% — multimodal understanding. For coding tasks that require visual understanding — UI mockups, architecture diagrams, chart analysis — Gemini is capable where Flash cannot compete.
- Google ecosystem integration. Native Google Search grounding, Workspace integration, and Vertex AI deployment. For teams in the Google Cloud ecosystem, Gemini is the path of least resistance.
- Toolathlon 49.4% vs 47.8% — edges Flash on tool diversity. A narrow but consistent lead on diverse tool-use tasks.
When to Use Which
| Scenario | Use | Why |
|---|---|---|
| Production bug fixing (real repos) | DeepSeek V4 Flash | 52.6% Pro vs 49.6%. +3.0 lead. |
| Algorithm & data structures | DeepSeek V4 Flash | 91.6% LiveCodeBench. 3052 Codeforces. |
| Cost-sensitive high-volume | DeepSeek V4 Flash | $0.28 vs $3.00. 10.7× cheaper. |
| Self-hosting / data sovereignty | DeepSeek V4 Flash | MIT license. Runs on your GPUs. |
| Agentic tool use (MCP) | DeepSeek V4 Flash | 69.0% vs 62.0%. +7.0 lead. |
| Scientific / ML coding | DeepSeek V4 Flash | 88.1% GPQA. +6.9 lead. |
| Code from images / video / audio | Gemini 3 Flash | Only one with multimodal input. |
| Desktop GUI automation | Gemini 3 Flash | 65.1% OSWorld. Verified computer use. |
| Google Cloud / Vertex AI teams | Gemini 3 Flash | Native ecosystem integration. |
| Chart & document understanding | Gemini 3 Flash | 80.3% CharXiv. 81.2% MMMU-Pro. |
Conclusion: Two Flash-Tier Models, Zero Overlap
DeepSeek V4 Flash is the better coding model. The 3-point Pro lead, 7-point Verified lead, 7-point MCP Atlas lead, and massive GPQA advantage are decisive. For pure software engineering — reading codebases, fixing bugs, implementing algorithms, using tools — Flash is stronger, cheaper, and open-weight. The 10.7× price gap makes it the default choice for any text-only coding workflow.
Gemini 3 Flash is the more versatile model. Multimodal input, computer use, and the Google ecosystem give it capabilities Flash cannot match. For coding from visual references, operating desktop applications, and workflows that span text + image + video, Gemini is the only option. It's also five months older — a Gemini 3 Flash successor may close the coding gap.
The Flash tier in 2026 splits into two lanes: the open-weight coding specialist (DeepSeek) and the multimodal generalist (Google). Choose the lane that fits your stack.
20+ LLMs available. Side-by-side testing. Both models ready.
Sources: DeepSeek V4 Model Card | Google Gemini 3.5 Flash Model Card (contains Gemini 3 Flash comparison data) | Gemini 3 Flash Review (Dec 2025) | Artificial Analysis | SWE-bench Pro Leaderboard | Terminal-Bench Leaderboard | V4 Flash vs GPT-5.4 Mini.