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Home/Best Gemini 3.7 Flash Alternatives
Best alternative: Claude Fable 5Alternatives

Best Gemini 3.7 Flash Alternatives

Claude Fable 5 is the strongest alternative to Gemini 3.7 Flash — it scores 99 vs 90 on long-context work at $10/1M input (Gemini 3.7 Flash costs $0.75/1M). DeepSeek V4-Pro is the budget swap: $0.435/1M input is 42% cheaper. Kimi K3 is the top open-weight option if you want a model you can self-host.

Last verified Aug 27, 2026/Model data modified Aug 27, 2026
Rankings refresh dailyScored on 6 criteriaNo paid rankings
AnthropicPremium
Input cost
$10.00/1M
Context
1M tokens
Speed
Deliberate

Clear recommendation block

The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.

Best overall model

Claude Fable 5

View
Why this recommendation

Claude Fable 5 is the safest overall answer here when you want the strongest default instead of the lowest list price.

AnthropicPremium
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Price
$10.00/1M
Context
1M tokens
Best budget model

Mistral: Mistral Nemo

View
Why this recommendation

Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.

MistralBudget
Best for
Teams needing a cheap, fast, multilingual workhorse for classification, summarization, or light coding tasks at scale.
Price
$0.02/1M
Context
131k tokens
Best for speed

Gemini 3.7 Flash

View
Why this recommendation

Gemini 3.7 Flash is the better pick when response speed matters more than maximum reasoning depth.

GoogleBalanced
Best for
High-volume coding and long-context work at introductory Flash pricing
Price
$0.75/1M
Context
1.0M tokens

Why this page recommends it

Claude Fable 5 beats Gemini 3.7 Flash on long-context work (99 vs 90) at $10/1M input tokens.

DeepSeek V4-Pro cuts input cost by 42% ($0.435 vs $0.75/1M) while scoring 90/100 on long-context work.

Kimi K3 is open-weight — self-host it or run it via low-cost API providers at $3/1M input.

Decision notes

Choose Claude Fable 5 when you want the closest overall replacement — it targets the hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning.

Choose DeepSeek V4-Pro when token volume matters more than peak quality — it is 42% cheaper on input.

Staying with Google? Gemini 3.1 Pro is the strongest in-house switch at $2/1M input.

Interactive decision lab

Test the recommendation against your priority

Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.

#1Claude Fable 591 pts
#2Kimi K388 pts
#3Gemini 3.1 Pro86 pts
#4Gemini 3.7 Flash85 pts
#5DeepSeek V4-Pro83 pts
Quality first

Claude Fable 5

Anthropic / Premium / Jun 9, 2026

91

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.

Cost
$10.00/1M
$50.00/1M out
Speed
Deliberate
2/5 score
Context
1M tokens
input window
View model
Data-backed recommendation
Avoid this pick if

You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.

Recommended comparisons

The fastest way to see where the recommendation shifts when your priority changes.

GoogleBalancedBest alternative: Claude Fable 5

Gemini 3.7 Flash

80.8% SWE-bench Verified at introductory Flash pricing.

Best use case
High-volume coding and long-context work at introductory Flash pricing
Input
$0.75/1M
Pricing
Balanced
Speed
Fast
Context
1.0M tokens
Coding1M contextFast
AnthropicPremiumOption 2

Claude Fable 5

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

Best use case
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Input
$10.00/1M
Pricing
Premium
Speed
Deliberate
Context
1M tokens
Coding leaderSWE-Bench Pro #1Mythos-class
DeepSeekBudgetOption 3

DeepSeek V4-Pro

Best open-weights flagship — near-frontier coding at a tenth of the price.

Best use case
Frontier-level coding and reasoning on a budget
Input
$0.43/1M
Pricing
Budget
Speed
Balanced
Context
1M tokens
Open weightsCodingReasoning
MoonshotPremiumOption 4

Kimi K3

Closest Chinese challenger to the frontier — #4 overall on intelligence.

Best use case
Frontier-level reasoning and agentic coding
Input
$3.00/1M
Pricing
Premium
Speed
Deliberate
Context
1M tokens
Open weightsReasoningFlagship
GooglePremiumOption 5

Gemini 3.1 Pro

Best for research and deep document analysis — 2M context at the best premium price.

Best use case
Research, deep document analysis, and long-context reasoning at competitive pricing
Input
$2.00/1M
Pricing
Premium
Speed
Balanced
Context
2M tokens
Research leader2M contextBest value premium

Side-by-side specs

Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.

ModelInputOutputEst. monthContextSpeedCodingWritingResearch
Claude Fable 5Anthropic$10.00/1M$50.00/1M$2001M tokensDeliberate10098100
Gemini 3.7 FlashGoogle$0.75/1M$3.75/1M$151.0M tokensFast898285
DeepSeek V4-ProDeepSeek$0.43/1M$0.87/1M$6.091M tokensBalanced938085
Kimi K3Moonshot$3.00/1M$15.00/1M$601M tokensDeliberate969093

Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.

The case for each model

What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.

Claude Fable 5

Best alternative: Claude Fable 5Anthropic

Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.

Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate

What people actually use it for

  • Autonomous agents that plan, write, run, and debug across an entire codebase with minimal supervision
  • Whole-repo refactors and PR review where accuracy outranks latency or cost
  • Frontier reasoning over 1M-token corpora — security audits, legal discovery, scientific synthesis

Where it wins

  • 80.3% SWE-Bench Pro — the new #1, up from Opus 4.8's 69.2% and GPT-5.5's 58.6%
  • 1932 on GDPval-AA, ahead of Opus 4.8 (1890) and GPT-5.5 (1769)
  • 1M-token context at standard pricing, 128K max output per request
  • Mythos-class capability released for general use with new cyber-risk safeguards

Where it falls down

  • Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25)
  • Deliberate pace; not for latency-sensitive interactive apps
  • Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access)

Skip it if

You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.

Our verdict

The strongest coding and reasoning model you can actually use today. 80.3% SWE-Bench Pro is an 11-point leap over Opus 4.8 — the biggest single-release jump of 2026. It costs 2× Opus 4.8, so use it for the hardest agentic and engineering work and keep Opus 4.8 or Sonnet for everyday volume.

Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.

Gemini 3.7 Flash

Google

Google's fastest-moving coding workhorse — 80.8% on SWE-bench Verified at half the price of Gemini 3.6 Flash, shipped just three weeks after it.

Input
$0.75/1M
Output
$3.75/1M
Context
1.0M tokens
Speed
Fast

What people actually use it for

  • Bulk code review and refactoring where 80.8% SWE-bench Verified is enough and volume matters
  • 1M-context document and repository analysis at $0.75/1M input
  • Agentic loops that need frontier-adjacent coding quality without frontier pricing

Where it wins

  • 80.8% on SWE-bench Verified — frontier-class coding from a Flash-tier model
  • Large jumps over 3.6 Flash on software engineering: FrontierCode 34.4% to 43.6%, DeepSWE 49.0% to 65.3%
  • Artificial Analysis Intelligence Index of 56 at high thinking level, with a 1M token context window

Where it falls down

  • The $0.75/$3.75 launch price is introductory — it doubles to $1.50/$7.50 on January 1, 2027
  • Still short of Claude Opus 5 (96%) and GPT-5.6 Sol (96.2%) on SWE-bench Verified for the hardest coding work

Skip it if

You are planning 2027 spend and need price certainty — the introductory rate expires December 31, 2026.

Our verdict

The best coding score per dollar in Google's lineup right now — 80.8% SWE-bench Verified at $0.75/1M input. Budget on the post-January 2027 price of $1.50/$7.50 if you are signing anything long-term.

Released August 13, 2026, only three weeks after Gemini 3.6 Flash. Introductory pricing of $0.75/$3.75 runs through December 31, 2026; on January 1, 2027 it doubles to $1.50/$7.50, which is exactly Gemini 3.6 Flash's rate.

DeepSeek V4-Pro

DeepSeek

DeepSeek's 1.6T-parameter (49B active) MoE flagship with hybrid sparse attention — near-frontier coding and reasoning at roughly a tenth of closed-rival pricing, MIT-licensed open weights.

Input
$0.43/1M
Output
$0.87/1M
Context
1M tokens
Speed
Balanced

What people actually use it for

  • Repository-level coding — 80.6% SWE-bench Verified (self-reported), the top open-weights score at release
  • Competitive-programming-grade reasoning (Codeforces rating 3206)
  • Self-hosted frontier capability under an MIT license

Where it wins

  • 80.6% SWE-bench Verified (self-reported) — reported as tied with Gemini 3.1 Pro
  • 93.5% LiveCodeBench and Codeforces 3206 — elite competitive-coding results
  • 1M context with 384K max output at $0.87/1M output — an order of magnitude cheaper than closed frontier models

Where it falls down

  • Independent harnesses report much lower agentic scores than the self-reported numbers; trails GPT-5.6 and Opus-class on hard agentic evals
  • Peak-hour surge pricing doubles rates, a price increase is announced, and it's text-only (no vision)

Skip it if

You need vision input, verified agentic performance, or predictable pricing (surge pricing and an announced increase loom).

Our verdict

The open-weights frontier flagship of 2026. Self-reported numbers flatter it and independent agentic scores land lower, but even discounted it's the most capability per dollar in the directory's upper tier — with MIT-licensed weights.

Open-weight preview April 24; GA ~July 20, 2026. Off-peak pricing verified on api-docs.deepseek.com; Beijing-business-hours surge doubles it. Legacy deepseek-chat/reasoner endpoints retired July 24, 2026.

Kimi K3

Moonshot

Moonshot's 2.8-trillion-parameter multimodal reasoning flagship with always-on thinking — the largest open-weight model ever released and the closest Chinese challenger to the Western frontier.

Input
$3.00/1M
Output
$15.00/1M
Context
1M tokens
Speed
Deliberate

What people actually use it for

  • Hardest reasoning tasks — #4 of all models on AA Intelligence Index v4.1 (57.1), ahead of Claude Opus 4.8
  • Agentic coding at 81.2 FrontierSWE and 88.3 Terminal-Bench 2.0 (Moonshot-reported)
  • 1M-context research synthesis with always-on extended thinking

Where it wins

  • AA Intelligence Index v4.1: 57.1 — #4 overall, behind only Claude Fable 5 and GPT-5.6 Sol, ahead of Claude Opus 4.8
  • FrontierSWE 81.2 and Terminal-Bench 2.0 88.3 — frontier-grade agentic coding numbers
  • Open weights (July 26, 2026) — at 2.8T parameters, the largest open-weight release in history

Where it falls down

  • Most expensive Chinese-lab model ever ($3/$15) with always-on thinking driving high output-token burn and slow responses
  • 2.8T size makes self-hosting impractical despite open weights; consumer signups were paused July 19 over GPU capacity

Skip it if

You need fast responses or predictable output costs — always-on thinking burns tokens.

Our verdict

The first Chinese model to genuinely crowd the Western frontier — #4 on aggregate intelligence ahead of Opus 4.8. The always-on thinking makes it slow and output-heavy, so cost per task runs above the sticker price. A serious Opus-class alternative if latency isn't critical.

Released July 16, 2026; open weights July 26. Cache-hit input $0.30/1M. Subscriptions: Adagio (free) to Vivace $199/mo; full 1M context only on Allegro ($99) and up. New signups paused July 19 near GPU capacity, reopening in batches.

Explore related decisions

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Gemini 3.7 Flash80.8% SWE-bench Verified at introductory Flash pricing.Read guide
Anthropic
Claude Fable 5New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.Read guide
Comparison
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Browse all modelsCompare pricingView Gemini 3.7 FlashView Claude Fable 5View DeepSeek V4-Pro

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FAQ

What is the best alternative to Gemini 3.7 Flash?

Claude Fable 5 is the strongest overall alternative. It scores 99/100 on long-context work (Gemini 3.7 Flash: 90/100) and costs $10/1M input vs $0.75/1M. New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

What is the cheapest good alternative to Gemini 3.7 Flash?

DeepSeek V4-Pro at $0.435/1M input — 42% cheaper than Gemini 3.7 Flash's $0.75/1M. It scores 90/100 on long-context work, so expect a quality step down on the hardest tasks.

Is there an open-source alternative to Gemini 3.7 Flash?

Yes — Kimi K3 is the strongest open-weight replacement for Gemini 3.7 Flash, scoring 93/100 on long-context work against Gemini 3.7 Flash's 90/100. You can self-host it or run it through hosted APIs at $3/1M input (Gemini 3.7 Flash costs $0.75/1M), with no per-seat subscription. Self-hosting trades the licence saving for infrastructure you have to run, so it pays off at sustained volume rather than for occasional use.

What is the best Google alternative to Gemini 3.7 Flash?

Gemini 3.1 Pro — same provider, same API surface, $2/1M input vs $0.75/1M. Best for research and deep document analysis — 2M context at the best premium price.

Is Gemini 3.7 Flash still worth using in 2026?

The best coding score per dollar in Google's lineup right now — 80.8% SWE-bench Verified at $0.75/1M input.