Grok 4.3 vs Gemini 3.1 Pro: Budget Frontier vs Google's Multimodal Workhorse in May 2026
xAI shipped Grok 4.3 on April 30 with steep price cuts and native video input. Google's Gemini 3.1 Pro Preview carries a higher Intelligence Index and the only published SWE-bench Pro score in this comparison. Here is how to choose between them.
xAI released Grok 4.3 on April 30, 2026. Google released Gemini 3.1 Pro as a Preview earlier that month. Both target production enterprise workloads from fundamentally different positions. Grok 4.3 ships at $1.25 per million input tokens and $2.50 per million output tokens, the cheapest closed frontier model available. Gemini 3.1 Pro ships at $2.50 input and $10.00 output, with a higher Artificial Analysis Intelligence Index (57 vs 53), a published SWE-bench Pro score of 54.2%, and native multimodal coverage across text, image, video, and audio.
This comparison is not about finding a winner. It is about understanding which model fits which workload. Grok leads on cost per output token, domain benchmarks in legal and finance, and native video input. Gemini leads on overall intelligence index, verified agentic coding scores, and the full multimodal surface including audio.
The Models at a Glance
| Grok 4.3 | Gemini 3.1 Pro | |
|---|---|---|
| Release | April 30, 2026 | April 2026 (Preview) |
| Context window | 1M tokens | 1M tokens |
| Multimodal input | Text, image, native video | Text, image, video, audio |
| Headline capability | Native video input, low cost | Intelligence index lead, native audio |
| Availability | xAI API, OpenRouter | Google AI Studio, Vertex AI |
| Input pricing (per 1M) | $1.25 | $2.50 |
| Output pricing (per 1M) | $2.50 | $10.00 |
| Intelligence Index (Artificial Analysis) | 53 | 57 |
What Each Release Changed
Grok 4.3
The price cut from Grok 4.20 is the most consequential change. Input dropped roughly 40% and output dropped roughly 60%. xAI is positioning Grok 4.3 as the cost leader among closed frontier models, with capability close enough to the frontier to be defensible for a wide range of production workloads.
Native video input arrived with 4.3 as an xAI first. The model processes video frames through a vision encoder without an external transcription or sampling pipeline. This simplifies the architecture for any workflow involving video content.
On benchmarks, Grok 4.3 leads CaseLaw v2 at 79.3% and CorpFin among published numbers, and posts a 1500 ELO on GDPval-AA, ahead of Gemini 3.1 Pro Preview on that metric. The Artificial Analysis Intelligence Index score of 53 trails Gemini 3.1 Pro (57), but the price gap is 2x on input and 4x on output.
Gemini 3.1 Pro
Gemini 3.1 Pro Preview carries an Intelligence Index of 57, tied with Claude Opus 4.7 on that metric, and substantially higher than Grok 4.3's 53. SWE-bench Pro at 54.2% is a verified agentic coding score that Grok 4.3 has not published a comparable number against.
The native multimodal architecture covers text, image, video, and audio without external preprocessing. For workflows that need audio understanding natively in a single API call, Gemini 3.1 Pro is currently the only major closed model that supports it alongside video.
Gemini 3.1 Pro is deeply integrated into Vertex AI and Google Cloud, with enterprise compliance posture (SOC 2 Type II, HIPAA BAA) available for teams that need it.
Benchmark Comparison
| Benchmark | Grok 4.3 | Gemini 3.1 Pro | Edge |
|---|---|---|---|
| Artificial Analysis Intelligence Index | 53 | 57 | Gemini |
| SWE-bench Pro | not directly reported | 54.2% | Gemini |
| GDPval-AA (ELO) | 1500 | below 1500 | Grok |
| CaseLaw v2 | 79.3% (#1) | not directly reported | Grok |
| CorpFin | #1 | not directly reported | Grok |
Gemini leads on the published agentic coding and general intelligence metrics. Grok leads on the published legal and financial domain benchmarks. The two models do not publish against the same benchmark suites, which limits a clean apples to apples comparison. The headline pattern is clear: Gemini 3.1 Pro carries the higher general capability signal, Grok 4.3 leads on domain specialist benchmarks at a substantially lower price.
Multimodal Capability
Gemini 3.1 Pro's multimodal coverage is broader. Text, image, video, and audio are all native inputs. For workflows that need audio understanding as a first class signal, Gemini is the only model in this comparison that handles it without an external preprocessing step. The audio architecture is inherited from Google's native Gemini design rather than bolted on.
Grok 4.3 introduced native video input with this release. The model processes video frames through a vision encoder in a single API call. Audio input is not part of the Grok 4.3 surface.
For image input, Gemini 3.1 Pro carries Google's accumulated advantage in vision. For video only workflows, either model handles it natively. For audio, Gemini is the only option in this comparison.
Agentic Capability
Gemini 3.1 Pro has the stronger published agentic coding case. SWE-bench Pro at 54.2% is a verified score on real repository code editing. Grok 4.3 has not published a direct SWE-bench Verified or SWE-bench Pro number.
Grok 4.3's GDPval-AA ELO of 1500 is a strong signal on agentic professional work in non coding domains, legal research, financial analysis, and general knowledge work. That score trails Gemini 3.1 Pro on SWE-bench but leads on the GDPval-AA metric.
For engineering agents operating on real codebases, Gemini 3.1 Pro has the stronger published case. For agents in legal, finance, or professional knowledge work domains, Grok 4.3 is competitive at a much lower price point.
Pricing and Total Cost
| Grok 4.3 | Gemini 3.1 Pro | |
|---|---|---|
| Input per 1M | $1.25 | $2.50 |
| Output per 1M | $2.50 | $10.00 |
| Vertex AI managed inference | not available | available |
| Enterprise compliance | limited | SOC 2, HIPAA BAA |
At list prices, Grok 4.3 is 2x cheaper on input and 4x cheaper on output. The practical gap is meaningful at scale. A workload generating 100 million output tokens per month costs $250 on Grok 4.3 and $1,000 on Gemini 3.1 Pro before any discounts. At 1 billion output tokens monthly, the gap is $2,500 versus $10,000.
The Gemini offset is quality on agentic coding tasks and audio input. If your workload produces higher accuracy on Gemini per output token, fewer tokens are needed to reach a reliable result, which partially narrows the cost gap. Run your own token economics model against your production prompts before committing based on list rates.
Direct Comparison Table
| Category | Grok 4.3 | Gemini 3.1 Pro | Edge |
|---|---|---|---|
| Intelligence Index | 53 | 57 | Gemini |
| Agentic coding (SWE-bench Pro) | not directly reported | 54.2% | Gemini |
| Legal / finance domain | strongest published | not directly reported | Grok |
| Native video input | yes | yes | Tie |
| Native audio input | no | yes | Gemini |
| Native image input | yes | yes | Tie |
| Context window | 1M | 1M | Tie |
| Input price (per 1M) | $1.25 | $2.50 | Grok |
| Output price (per 1M) | $2.50 | $10.00 | Grok |
| Vertex AI managed inference | no | yes | Gemini |
| Enterprise compliance | limited | SOC 2, HIPAA | Gemini |
| GDPval-AA ELO | 1500 | below 1500 | Grok |
Which One Should You Use
Use Grok 4.3 when:
- Cost per output token is the dominant variable
- Native video input is a core requirement
- Your workload is legal research, financial analysis, or general professional knowledge work
- You can absorb the general capability gap for a 4x output price advantage
- You are building high volume generation pipelines where token costs dominate
Use Gemini 3.1 Pro when:
- Agentic coding on real codebases is the primary workload
- Native audio input is required in a single API call
- You need the higher Intelligence Index for general reasoning tasks
- Vertex AI managed inference and Google Cloud compliance posture matter
- Your stack is GCP anchored and the ecosystem integration reduces overhead
Use both when:
- Grok 4.3 handles high volume generation, video processing, and legal or financial analysis
- Gemini 3.1 Pro handles agentic coding stages, audio workflows, and hard reasoning tasks
- Route by task shape rather than provider loyalty
Our Default for May 2026
For agentic coding work and general reasoning, Gemini 3.1 Pro holds the higher published capability signal in this comparison. The Intelligence Index of 57 and SWE-bench Pro of 54.2% are the stronger disclosed numbers for workloads that need verified agentic performance on real codebases. The audio input surface covers workflows that Grok 4.3 cannot handle natively.
For cost sensitive high volume workloads, video input pipelines, and legal or financial domain work, Grok 4.3 is the stronger option. The 2x input and 4x output price gap to Gemini 3.1 Pro is large enough that the routing decision becomes obvious on workloads that do not require verified agentic coding performance or native audio.
A durable AI architecture in May 2026 uses Grok 4.3 where cost per token and video input drive the decision, and reaches for Gemini 3.1 Pro where agentic capability, audio, and the Google Cloud ecosystem compound into downstream value.
How Contra Collective Bridges the Gap
Contra Collective runs Grok 4.3, Gemini 3.1 Pro, Opus 4.7, GPT-5.5, Gemma 4, and Qwen 3.6 in production across coding pipelines, multimodal content systems, and multi agent workflows for enterprise clients. We architect systems that use the right model at each stage rather than defaulting to a single provider. Ready to make the right call for your stack? Book a free technical audit, no sales pitch, just clarity.
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