TokenMix Research Lab · 2026-04-24

GPT-5 vs Gemini 3 2026: 10 Benchmarks Head-to-Head

GPT-5 vs Gemini 3 2026: 10 Benchmarks Head-to-Head

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/ 2 beats GPT-5.4's $2.50/ 5. 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

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/ 2 per MTok Confirmed
GPT-5.4 $2.50/ 5 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%

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 2.00 $4.00
GPT-5.4 $2.50 5.00 $5.00
Gemini 3.1 Flash $0.30 .20 $0.48
GPT-5.4-mini $0.25 .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:

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 0 (20%)
500M tokens/month $2,500 $2,000 $500 (20%)
10B tokens/month $50,000 $40,000 0,000 (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/ 2 — 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"?

Coming, not released as of April 2026. See GPT-5.5 release date. Whether it closes the gap with Gemini 3.1 Pro depends on its SWE-Bench improvements.

Sources

By TokenMix Research Lab · Updated 2026-04-24