DeepSeek V4 Pro vs Gemini 4 Argon vs Gemini Robotics-ER 1.6 Preview
Gemini 4 Argon comes out ahead, 52 to 46 and 39 on our weighted score, though Gemini Robotics-ER 1.6 Preview is 2× cheaper per token.
DeepSeek
DeepSeek V4 Pro
39/100- ECI—
- Price$1.60 / $3.30
- Context1M
- Our pick
Google
Gemini 4 Argon
52/100- ECI166.1
- Price$2.00 / $10.00
- Context1.05M
Google
Gemini Robotics-ER 1.6 Preview
46/100- ECI—
- Price$1.00 / $5.00
- Context131K
Gemini 4 Argon is our pick
Gemini 4 Argon is the better all-round choice, scoring 52/100 against Gemini Robotics-ER 1.6 Preview (46) and DeepSeek V4 Pro (39). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGemini Robotics-ER 1.6 PreviewGemini Robotics-ER 1.6 Preview $2.00 · DeepSeek V4 Pro $2.03 · Gemini 4 Argon $4.00 per 1M tokens (3:1 blend)
- Longest contextGemini 4 ArgonGemini 4 Argon 1,048,576 · DeepSeek V4 Pro 1,000,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsGemini 4 ArgonDeepSeek V4 Pro: Text · Gemini 4 Argon: Text, Images, PDFs, Audio, Video · Gemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video
- Self-hostingDeepSeek V4 ProPublishes downloadable weights
| Measure | Weight | DeepSeek V4 Pro | Gemini 4 Argon | Gemini Robotics-ER 1.6 Preview |
|---|---|---|---|---|
| Price | 50% | 34 | 20 | 34 |
| Inputs & features | 30% | 35 | 100 | 80 |
| Context window | 20% | 60 | 61 | 25 |
| Overall | 100% | 39/100 | 52/100 | 46/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 166.1 | — |
| ECI rank | — | #7 of 165 | — |
| GPQA DiamondGraduate-level science questions | — | 96.4% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 86.0% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 100% | — |
| SimpleQA VerifiedShort factual questions | — | 76.0% | — |
| Price per million tokens | |||
| Input | $1.60 | $2.00 | $1.00 (best) |
| Output | $3.30 (best) | $10.00 | $5.00 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $2.03 | $4.00 | $2.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 56 providers | Official Google API | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) | 131,072 tokens |
| Max output | 384,000 tokens (best) | 65,536 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | Yes | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | gemini-4-argon | — |
| API providers | 58 (best) | 24 | 1 |
| Released | Apr 24, 2026 | Oct 13, 2026 | Apr 14, 2026 |
| Knowledge cutoff | May 2025 | Mar 2026 | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
DeepSeek V4 Pro$22.60
Gemini 4 Argon$40.00
Gemini Robotics-ER 1.6 Preview$20.00
Which should you choose?
Which is better: DeepSeek V4 Pro, Gemini 4 Argon or Gemini Robotics-ER 1.6 Preview?
Gemini 4 Argon is the better all-round choice, scoring 52/100 against Gemini Robotics-ER 1.6 Preview (46) and DeepSeek V4 Pro (39). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek V4 Pro, Gemini 4 Argon or Gemini Robotics-ER 1.6 Preview?
Gemini Robotics-ER 1.6 Preview is cheaper at $1.00 input / $5.00 output per million tokens (median across 1 API provider). DeepSeek V4 Pro costs $1.60 input / $3.30 output per million tokens (median across 56 API providers); Gemini 4 Argon costs $2.00 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $2.00 per million tokens for Gemini Robotics-ER 1.6 Preview versus $2.03 for DeepSeek V4 Pro (1× as much) and $4.00 for Gemini 4 Argon (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek V4 Pro has not been scored yet, Gemini 4 Argon has an ECI of 166.1 and Gemini Robotics-ER 1.6 Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Pro, Gemini 4 Argon and Gemini Robotics-ER 1.6 Preview yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 4 Argon has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4 Pro and 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: DeepSeek V4 Pro up to 384,000, Gemini 4 Argon up to 65,536, Gemini Robotics-ER 1.6 Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Pro accepts text; Gemini 4 Argon accepts text, images, PDFs, audio and video; Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video. Gemini 4 Argon handles the widest range of inputs.
Are any of these open source?
DeepSeek V4 Pro publishes its weights and can be self-hosted; Gemini 4 Argon and Gemini Robotics-ER 1.6 Preview is proprietary.
Which is newer?
Gemini 4 Argon is the newest, released Oct 13, 2026. DeepSeek V4 Pro came out Apr 24, 2026; Gemini Robotics-ER 1.6 Preview came out Apr 14, 2026. Knowledge cutoff: DeepSeek V4 Pro May 2025, Gemini 4 Argon Mar 2026, Gemini Robotics-ER 1.6 Preview Jan 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.