TokenMix Research Lab · 2026-04-24
GPT-5 vs Gemini 3 2026: 10 Benchmarks Head-to-Head
Last Updated: 2026-04-29
Author: TokenMix Research Lab
OpenAI's GPT-5 and Google's Gemini 3 are the two major non-Anthropic frontier model families in 2026. Both launched within a few months of each other (GPT-5 Aug 2025, Gemini 3 Oct 2025) and both have evolved — current flagships are GPT-5.4 and Gemini 3.1 Pro. Benchmark-wise: Gemini 3.1 Pro leads on GPQA Diamond (94.3% vs 92.8%), GPT-5.4 leads on HumanEval (93.1% vs ~92%), and they tie on MMLU (~90%). Pricing: Gemini 3.1 Pro at $2/$12 beats GPT-5.4's $2.50/$15. This comprehensive comparison covers 10 benchmarks, context windows (1M vs 272K), multimodal, cost math, and the specific decision matrix. TokenMix.ai runs both via OpenAI-compatible endpoint.
Table of Contents
- Confirmed vs Speculation
- 10-Benchmark Side-by-Side
- Pricing Comparison
- Long Context: 1M vs 272K
- Multimodal Capabilities
- Cost Math at 3 Scales
- Decision Matrix
- FAQ
Confirmed vs Speculation
| Claim | Status |
|---|---|
| GPT-5.4 is current OpenAI flagship | Confirmed (March 2026) |
| Gemini 3.1 Pro is current Google flagship | Confirmed (Feb 2026) |
| Gemini 3.1 Pro $2/$12 per MTok | Confirmed |
| GPT-5.4 $2.50/$15 | Confirmed |
| Gemini 3.1 Pro has 1M context | Confirmed |
| GPT-5.4 has 272K context | Confirmed |
| Gemini 3.1 Pro GPQA 94.3% | Confirmed |
| GPT-5.4 Thinking beats Gemini on OSWorld | Yes 75% vs ~72% |
Snapshot note (2026-04-24): GPT-5.5 launched April 23, 2026 and doubled GPT-5 family per-token prices to $5/$30 — this comparison uses GPT-5.4 pricing and is pre-GPT-5.5. Benchmark percentages for GPT-5.4 (SWE-Bench Verified 58.7%, HumanEval 93.1%, OSWorld 75%) and Gemini 3.1 Pro (GPQA 94.3%, SWE-Bench 80.6%) aggregate launch-post vendor numbers with third-party leaderboards — read as vendor-aligned. Gemini 3.1 Pro $2/$12 and context 1M are Google-confirmed.
10-Benchmark Side-by-Side
| Benchmark | GPT-5.4 | Gemini 3.1 Pro | Winner |
|---|---|---|---|
| MMLU | 90% | 91% | Gemini (marginal) |
| GPQA Diamond | 92.8% | 94.3% | Gemini |
| HumanEval | 93.1% | 92% | GPT-5.4 |
| SWE-Bench Verified | 58.7% | 80.6% | Gemini +22pp |
| MATH-500 | 92% | 93% | Gemini |
| LiveCodeBench | 85% | 84% | GPT-5.4 (marginal) |
| OSWorld (computer use) | 75% (Thinking mode) | 72% | GPT-5.4 |
| Long-context recall @ 128K | 92% | 93% | Gemini |
| Long-context recall @ 1M | N/A (272K max) | ~70% | Gemini (only option) |
| Vision (MMBench) | 88% | 89% | Gemini |
Score: Gemini 3.1 Pro wins 7, GPT-5.4 wins 3. Gemini is meaningfully stronger on coding (SWE-Bench Verified +22pp), general knowledge, vision, and long context.
Pricing Comparison
| Model | Input $/MTok | Output $/MTok | Blended (80/20) |
|---|---|---|---|
| Gemini 3.1 Pro | $2.00 | $12.00 | $4.00 |
| GPT-5.4 | $2.50 | $15.00 | $5.00 |
| Gemini 3.1 Flash | $0.30 | $1.20 | $0.48 |
| GPT-5.4-mini | $0.25 | $1.00 | $0.40 |
Gemini 3.1 Pro is 20% cheaper than GPT-5.4. Combined with the SWE-Bench Verified advantage, Gemini wins on price-adjusted coding performance. OpenAI's advantage is brand / ecosystem integration / developer mindshare.
Long Context: 1M vs 272K
Gemini 3.1 Pro: 1,000,000 tokens (native) vs GPT-5.4: 272,000 tokens.
For workloads that genuinely need >272K context:
- Legal discovery across massive case files
- Analysis of full codebases in one prompt
- Long conversation history preservation
- Book-scale document analysis
Gemini 3.1 Pro is the default choice — cheaper per token AND longer context. GPT-4.1 offers 1M but trails on quality.
Caveat: recall at 1M drops to ~70%, so 1M isn't magic — combine with retrieval when accuracy matters.
Multimodal Capabilities
| Capability | GPT-5.4 | Gemini 3.1 Pro |
|---|---|---|
| Image input | Yes | Yes |
| Image generation | Via gpt-image-2 (separate) | Via imagen-4 (separate) |
| Audio input | Via realtime-preview | Native (Gemini Live) |
| Audio output | Via realtime-preview | Native (Flash TTS) |
| Video input | Frame-by-frame | Native long video |
| Document (PDF) | Via vision | Native document mode |
Gemini is more natively multimodal. For apps processing varied media types in a single pipeline, Gemini 3.1 Pro's unified API is simpler than stitching GPT-5.4 + GPT-4o-realtime + gpt-image-2.
Cost Math at 3 Scales
80/20 input/output:
| Workload | GPT-5.4 | Gemini 3.1 Pro | Savings with Gemini |
|---|---|---|---|
| 10M tokens/month | $50 | $40 | $10 (20%) |
| 500M tokens/month | $2,500 | $2,000 | $500 (20%) |
| 10B tokens/month | $50,000 | $40,000 | $10,000 (20%) |
At enterprise scale, 20% savings = meaningful budget line. For 500M tokens/month, $6K/year savings pays for 1 developer day/month.
Decision Matrix
| Your priority | Pick |
|---|---|
| Best coding benchmarks | Gemini 3.1 Pro (SWE-Bench +22pp) |
| Best general reasoning | Gemini 3.1 Pro (GPQA edge) |
| Best HumanEval score | GPT-5.4 (marginal) |
| Lowest cost per token | Gemini 3.1 Pro ($4 vs $5) |
| Longest native context | Gemini 3.1 Pro (1M vs 272K) |
| Best computer use | GPT-5.4 Thinking (OSWorld 75%) |
| Native audio I/O | Gemini 3.1 Pro (Live API) |
| Already on OpenAI stack | GPT-5.4 (zero migration) |
| Already on Google Cloud | Gemini 3.1 Pro |
| Most mature agent frameworks | GPT-5.4 (ecosystem) |
FAQ
Should I migrate my production from GPT-5.4 to Gemini 3.1 Pro?
Only if specific factors warrant: coding benchmark gap, long-context need, or Google Cloud integration. For existing OpenAI-integrated apps where migration cost is real, the 20% price + benchmark gains may not justify the switch unless scale is large.
Is Gemini 3.1 Pro better than Claude Opus 4.7 for coding?
Claude Opus 4.7 wins on SWE-Bench Verified (87.6% vs Gemini 3.1 Pro's 80.6%) but Opus is $5/$25 vs Gemini's $2/$12 — more than 2× cost. For pure coding, Opus. For balanced production, Gemini's price-adjusted value wins.
Can both handle 1M context equally well?
No. Gemini has native 1M. GPT-5.4 caps at 272K. For long context, Gemini is the OpenAI-adjacent option; Claude Opus 4.7's 1M mode (via beta flag) is the premium alternative.
What about GPT-4.1's 1M context?
GPT-4.1 offers 1M at $2/$8 — cheaper than both GPT-5.4 and Gemini 3.1 Pro, but with ~3pp lower benchmark scores than GPT-5.4. See GPT-4.1 vs 4o.
Which is faster?
Typical latency similar at p50 (2-3 seconds for short responses). Gemini 3.1 Flash is faster (<500ms TTFT) than both flagship models — use Flash variant for latency-critical chat.
Does Gemini support tool use / function calling?
Yes, native. OpenAI-compatible schema via LiteLLM, TokenMix.ai gateway, or Google's direct SDK. Competitive with GPT-5.4 on tool use quality.
What about GPT-5.5 "Spud"?
Released April 23, 2026 at $5/$30 per MTok (2× the GPT-5.4 list price). Hit 88.7% SWE-Bench Verified, 92.4% MMLU, with a 60% hallucination reduction and natively omnimodal architecture. This closes much of the SWE-Bench gap vs Gemini 3.1 Pro but at meaningfully higher cost. See GPT-5.5 full review for the comparison vs Gemini.
Sources
- OpenAI Models
- Google Gemini Docs
- GPT-5.4 Thinking Review — TokenMix
- Gemini 3.1 Pro Review — TokenMix
- Claude 4.5 vs ChatGPT-5 — TokenMix
- All ChatGPT Models — TokenMix
By TokenMix Research Lab · Updated 2026-04-24