Gemini 4 Argon vs DeepSeek V4 Pro vs Claude Sonnet 5.5
Gemini 4 Argon comes out ahead, 52 to 46 and 39 on our weighted score, though DeepSeek V4 Pro is 2× cheaper per token.
- Our pick
Google
Gemini 4 Argon
52/100- ECI166.1
- Price$2.00 / $10.00
- Context1.05M
DeepSeek
DeepSeek V4 Pro
39/100- ECI—
- Price$1.60 / $3.30
- Context1M
Anthropic
Claude Sonnet 5.5
46/100- ECI166.7
- Price$2.00 / $10.00
- Context1M
Gemini 4 Argon is our pick
Gemini 4 Argon is the better all-round choice, scoring 52/100 against Claude Sonnet 5.5 (46) and DeepSeek V4 Pro (39). It leads on inputs & features. DeepSeek V4 Pro wins on price. 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 priceDeepSeek V4 ProDeepSeek V4 Pro $2.03 · Gemini 4 Argon $4.00 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextGemini 4 ArgonGemini 4 Argon 1,048,576 · DeepSeek V4 Pro 1,000,000 · Claude Sonnet 5.5 1,000,000 tokens
- Widest inputsGemini 4 ArgonGemini 4 Argon: Text, Images, PDFs, Audio, Video · DeepSeek V4 Pro: Text · Claude Sonnet 5.5: Text, Images, PDFs
- Self-hostingDeepSeek V4 ProPublishes downloadable weights
| Measure | Weight | Gemini 4 Argon | DeepSeek V4 Pro | Claude Sonnet 5.5 |
|---|---|---|---|---|
| Price | 50% | 20 | 34 | 20 |
| Inputs & features | 30% | 100 | 35 | 80 |
| Context window | 20% | 61 | 60 | 60 |
| Overall | 100% | 52/100 | 39/100 | 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 | — | 166.7 (best) |
| ECI rank | #7 of 165 | — | #5 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 96.4% (best) | — | 95.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 86.0% | — | 88.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% | — | 100% |
| SimpleQA VerifiedShort factual questions | 76.0% (best) | — | 46.5% |
| Price per million tokens | |||
| Input | $2.00 | $1.60 (best) | $2.00 |
| Output | $10.00 | $3.30 (best) | $10.00 |
| Cached input | $0.10 | — | $0.10 |
| Blended (3:1) | $4.00 | $2.03 (best) | $4.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Median of 56 providers | Official Anthropic API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 65,536 tokens | 384,000 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yeslow · medium · high | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gemini-4-argon | — | claude-sonnet-5-5 |
| API providers | 24 | 58 (best) | 34 |
| Released | Oct 13, 2026 | Apr 24, 2026 | Sep 28, 2026 |
| Knowledge cutoff | Mar 2026 | May 2025 | Jun 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemini 4 Argon$40.00
DeepSeek V4 Pro$22.60
Claude Sonnet 5.5$40.00
Which should you choose?
Which is better: Gemini 4 Argon, DeepSeek V4 Pro or Claude Sonnet 5.5?
Gemini 4 Argon is the better all-round choice, scoring 52/100 against Claude Sonnet 5.5 (46) and DeepSeek V4 Pro (39). It leads on inputs & features. DeepSeek V4 Pro wins on price. 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, Gemini 4 Argon, DeepSeek V4 Pro or Claude Sonnet 5.5?
DeepSeek V4 Pro is cheaper at $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); Claude Sonnet 5.5 costs $2.00 input / $10.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $2.03 per million tokens for DeepSeek V4 Pro versus $4.00 for Gemini 4 Argon (2× as much) and $4.00 for Claude Sonnet 5.5 (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 4 Argon has an ECI of 166.1, DeepSeek V4 Pro has not been scored yet and Claude Sonnet 5.5 has an ECI of 166.7.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 4 Argon, DeepSeek V4 Pro and Claude Sonnet 5.5 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 1,000,000 for Claude Sonnet 5.5. Maximum output per response: Gemini 4 Argon up to 65,536, DeepSeek V4 Pro up to 384,000, Claude Sonnet 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 4 Argon accepts text, images, PDFs, audio and video; DeepSeek V4 Pro accepts text; Claude Sonnet 5.5 accepts text, images and PDFs. 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 Claude Sonnet 5.5 is proprietary.
Which is newer?
Gemini 4 Argon is the newest, released Oct 13, 2026. Claude Sonnet 5.5 came out Sep 28, 2026; DeepSeek V4 Pro came out Apr 24, 2026. Knowledge cutoff: Gemini 4 Argon Mar 2026, DeepSeek V4 Pro May 2025, Claude Sonnet 5.5 Jun 2026.
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.