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Gemini 4 Argon (batch) vs GPT-6.1 Terra (batch)

Signal-by-Signal Comparison
SignalGemini 4 Argon (batch)DeltaGPT-6.1 Terra (batch)
Capabilities
100
--
100
Pricing
95
-2
98
Context window size
96
0
96
Recency
100
--
100
Output Capacity
96
+14
82
Overall Result
1 wins
of 5
2 wins
GPT-6.1 Terra (batch) wins 2 of 5 signals

Score History

Score History (3 data points)
Gemini 4 Argon (batch)GPT-6.1 Terra (batch)
Gemini 4 Argon (batch)

40

current score

Leader

Tied

right now

GPT-6.1 Terra (batch)

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Gemini 4 Argon (batch)

Google

Per request$0.003500
Daily$11.67
Monthly$350.00
Annual$4200.00

GPT-6.1 Terra (batch)

OpenAI

Best Value
Per request$0.001750
Daily$5.83
Monthly$175.00
Annual$2100.00

GPT-6.1 Terra (batch) saves you $175.00/month

That's $2100.00/year compared to Gemini 4 Argon (batch) at your current usage level of 100K calls/month.

50% cheaper
Choose GPT-6.1 Terra (batch) for cost optimization

Gemini 4 Argon (batch) pricing:
Input:$1.00/M tokens
Output:$5.00/M tokens
GPT-6.1 Terra (batch) pricing:
Input:$0.50/M tokens
Output:$2.50/M tokens
Tie
Gemini 4 Argon (batch)

Google

40

Composite Score

Tie
GPT-6.1 Terra (batch)

OpenAI

40

Composite Score

Signal-by-Signal Comparison
MetricGemini 4 Argon (batch)GPT-6.1 Terra (batch)Winner
Overall Score
40
40
--
Rank#202#183
GPT-6.1 Terra (batch)
Quality Rank#202#183
GPT-6.1 Terra (batch)
Adoption Rank#202#183
GPT-6.1 Terra (batch)
Parameters------
Context Window1049K1050K
GPT-6.1 Terra (batch)
Pricing$1.00/$5.00/M$0.50/$2.50/M--
Signal Scores
Capabilities
100
100
Gemini 4 Argon (batch)
Pricing
95
98
GPT-6.1 Terra (batch)
Context window size
96
96
GPT-6.1 Terra (batch)
Recency
100
100
Gemini 4 Argon (batch)
Output Capacity
96
82
Gemini 4 Argon (batch)
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Gemini 4 Argon (batch)Entry Level

Scores 40/100 (rank #202), placing it in the top 31% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GPT-6.1 Terra (batch)Entry Level

Scores 40/100 (rank #183), placing it in the top 37% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Gemini 4 Argon (batch) when you need:

  • Step-by-step reasoning and chain-of-thought problem solving

Choose GPT-6.1 Terra (batch) when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Gemini 4 Argon (batch)
Input cost$1.00/M tokens
Output cost$5.00/M tokens
Cost per quality point$0.150
Est. monthly (1M tokens/day)$90.00
GPT-6.1 Terra (batch)Best Value
Input cost$0.50/M tokens
Output cost$2.50/M tokens
Cost per quality point$0.075
Est. monthly (1M tokens/day)$45.00

GPT-6.1 Terra (batch) offers 50% better value per quality point. At 1M tokens/day, you'd spend $45.00/month with GPT-6.1 Terra (batch) vs $90.00/month with Gemini 4 Argon (batch) - a $45.00 monthly difference.

Latency & Speed
Gemini 4 Argon (batch)Faster
Speed score0/100
GPT-6.1 Terra (batch)
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Gemini 4 Argon (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. GPT-6.1 Terra (batch) also offers lower per-token costs for high-volume support

Gemini 4 Argon (batch)

Long document analysis

Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass

GPT-6.1 Terra (batch)

Batch data extraction

Lower output pricing ($2.50/M) reduces costs when processing thousands of records daily

GPT-6.1 Terra (batch)

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

Gemini 4 Argon (batch)

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Gemini 4 Argon (batch)
Which Should You Choose?
Our recommendation:
Gemini 4 Argon (batch)

Gemini 4 Argon (batch) and GPT-6.1 Terra (batch) are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Google

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by OpenAI

  • Choose for Cost - 50% lower pricing; better value at scale
Capability Comparison
CapabilityGemini 4 Argon (batch)GPT-6.1 Terra (batch)
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Gemini 4 Argon (batch)

Google

$7.80
estimated monthly cost

GPT-6.1 Terra (batch)

OpenAI

Best Value
$3.90
estimated monthly cost

GPT-6.1 Terra (batch) saves you $3.90/month

That's 50% cheaper than Gemini 4 Argon (batch) at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGemini 4 Argon (batch)GPT-6.1 Terra (batch)
Context Window1.0M1.1M
Max Output Tokens943,718128,000
Open SourceNoNo
CreatedOct 13, 2026Oct 26, 2026
Last updated: 33m ago

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Gemini 4 Argon (batch) vs GPT-6.1 Terra (batch) (2026) | LM Market Cap